Text Summarization – Meta-Guide.com

Notes:

Text summarization is the process of generating a shorter version of a longer text document while preserving its key information and main points. Text summarization can be useful for tasks such as information retrieval, content marketing, and news aggregation, where it is important to quickly understand the main points of a large number of texts.

There are several approaches to text summarization, including extractive summarization and abstractive summarization.

Extractive summarization involves selecting and extracting key sentences or phrases from the original text to form a summary. Extractive summarization can be implemented using techniques such as keyword extraction, sentence scoring, or graph-based methods. Extractive summarization is relatively simple to implement and can produce accurate summaries, but it is limited by the quality and coverage of the original text.

Abstractive summarization involves generating new sentences that capture the main ideas of the original text. Abstractive summarization can be implemented using techniques such as natural language generation or machine translation. Abstractive summarization is more challenging to implement but can produce more fluent and coherent summaries. However, it is prone to errors and may introduce factual inaccuracies or biases.

Text summarization can be a challenging task because it requires understanding the content and structure of the original text, identifying the important information, and generating a summary that is coherent and faithful to the original. It also requires a good understanding of the target audience and the purpose of the summary.

Text summarization can be used in dialog systems to generate concise and coherent summaries of information that the system has gathered from multiple sources. For example, a dialog system could use text summarization to generate a summary of a customer’s purchase history or to provide a summary of a news article that the user has requested.

Text summarization can be used in dialog systems to improve the user experience by reducing the amount of text that the user has to read or listen to. It can also help to make the dialog more efficient by providing only the most important information, rather than presenting the user with long lists of data or options.

Automatic text summarization is the process of generating a summary of a text document automatically, without human intervention. It is a subfield of natural language processing that involves developing algorithms and systems that can analyze and understand the content of a text and generate a summary that is coherent, faithful to the original, and concise.
Fuzzy relational clustering is a type of clustering method that is used to partition a dataset into groups, or clusters, of similar items. Fuzzy relational clustering is based on the idea of fuzzy sets, which allow for partial membership in a set. This means that an item can belong to more than one cluster to a certain degree, rather than being a member of a single cluster or not a member at all. Fuzzy relational clustering can be used for tasks such as image classification, document clustering, and data analysis.
Human aided machine summarization (HAMS) is a type of text summarization approach that involves combining the outputs of machine summarization with the input of a human to produce a final summary. In HAMS, the machine generates a summary of the text, which is then reviewed and edited by a human to ensure accuracy and coherence. HAMS can be useful for tasks where the quality of the summary is important and where the machine’s output needs to be refined by a human expert.
Machine aided human summarization (MAHS) is a type of text summarization approach that involves using machine learning techniques to assist a human in the summarization process. In MAHS, the machine generates a list of key sentences or phrases from the original text, which the human then uses to create a summary. MAHS can be useful for tasks where the human needs to be able to control the content of the summary, but where the machine can provide assistance in identifying important information.
Text summarizer is a tool or system that is used to generate a summary of a text document. Text summarizers can be implemented using a variety of techniques, including extractive summarization and abstractive summarization. Text summarizers can be used for tasks such as information retrieval, content marketing, and news aggregation, where it is important to quickly understand the main points of a large number of texts. Text summarizers can be implemented as standalone tools or integrated into larger systems, such as dialog systems or information retrieval systems.

Resources:

github.com/linanqiu/lexrank .. radev’s lexrank algorithm for unsupervised text summarization in node
sourceforge.net/projects/texminer .. text mining for texts in ascii, unicode and pdf format

Wikipedia:

References:

Abstractive text summarization using LSTM-CNN based deep learning
S Song, H Huang, T Ruan – Multimedia Tools and Applications, 2019 – Springer
Abstract Abstractive Text Summarization (ATS), which is the task of constructing summary sentences by merging facts from different source sentences and condensing them into a shorter representation while preserving information content and overall meaning. It is very …

Text summarization from legal documents: a survey
A Kanapala, S Pal, R Pamula – Artificial Intelligence Review, 2019 – Springer
Enormous amount of online information, available in legal domain, has made legal text processing an important area of research. In this paper, we attempt to survey different text summarization techniques that have taken place in the recent past. We put special emphasis …

Pretraining-based natural language generation for text summarization
H Zhang, Y Gong, Y Yan, N Duan, J Xu, J Wang… – arXiv preprint arXiv …, 2019 – arxiv.org
In this paper, we propose a novel pretraining-based encoder-decoder framework, which can generate the output sequence based on the input sequence in a two-stage manner. For the encoder of our model, we encode the input sequence into context representations using …

COSUM: Text summarization based on clustering and optimization
RM Alguliyev, RM Aliguliyev, NR Isazade… – Expert …, 2019 – Wiley Online Library
Text summarization is a process of extracting salient information from a source text and presenting that information to the user in a condensed form while preserving its main content. In the text summarization, most of the difficult problems are providing wide topic …

Graph-based text summarization using modified TextRank
C Mallick, AK Das, M Dutta, AK Das… – Soft Computing in Data …, 2019 – Springer
Nowadays, the efficient access of enormous amounts of information has become more difficult due to the rapid growth of the Internet. To manage the vast information, we need efficient and effective methods and tools. In this paper, a graph-based text summarization …

Evaluating the factual consistency of abstractive text summarization
W Kry?ci?ski, B McCann, C Xiong, R Socher – arXiv, 2019 – ui.adsabs.harvard.edu
Currently used metrics for assessing summarization algorithms do not account for whether summaries are factually consistent with source documents. We propose a weakly-supervised, model-based approach for verifying factual consistency and identifying conflicts …

A text summarization method based on fuzzy rules and applicable to automated assessment
FB Goularte, SM Nassar, R Fileto, H Saggion – Expert Systems with …, 2019 – Elsevier
In the last two decades, the text summarization task has gained much importance because of the large amount of online data, and its potential to extract useful information and knowledge in a way that could be easily handled by humans and used for a myriad of …

Text summarization with pretrained encoders
Y Liu, M Lapata – arXiv preprint arXiv:1908.08345, 2019 – arxiv.org
Bidirectional Encoder Representations from Transformers (BERT) represents the latest incarnation of pretrained language models which have recently advanced a wide range of natural language processing tasks. In this paper, we showcase how BERT can be usefully …

SummCoder: An unsupervised framework for extractive text summarization based on deep auto-encoders
A Joshi, E Fidalgo, E Alegre… – Expert Systems with …, 2019 – Elsevier
In this paper, we propose SummCoder, a novel methodology for generic extractive text summarization of single documents. The approach generates a summary according to three sentence selection metrics formulated by us: sentence content relevance, sentence novelty …

Generative adversarial network with policy gradient for text summarization
B Rekabdar, C Mousas, B Gupta – 2019 IEEE 13th international …, 2019 – ieeexplore.ieee.org
Abstractive text summarization is the task of generating meaningful summary from a given document (short or long). This is a very challenging task for longer documents, since they suffer from repetitions (redundancy) when the given document is long and the generated …

Sentence similarity estimation for text summarization using deep learning
S Abujar, M Hasan, SA Hossain – … of the 2nd International Conference on …, 2019 – Springer
One of the key challenges of natural language processing (NLP) is to identify the meaning of any text. Text summarization is one of the most challenging applications in the field of NLP where appropriate analysis is needed of given input text. Identifying the degree of …

Deep transfer reinforcement learning for text summarization
Y Keneshloo, N Ramakrishnan, CK Reddy – Proceedings of the 2019 SIAM …, 2019 – SIAM
Deep neural networks are data hungry models and thus face difficulties when attempting to train on small text datasets. Transfer learning is a potential solution but their effectiveness in the text domain is not as explored as in areas such as image analysis. In this paper, we …

Neural extractive text summarization with syntactic compression
J Xu, G Durrett – arXiv preprint arXiv:1902.00863, 2019 – arxiv.org
Recent neural network approaches to summarization are largely either sentence-extractive, choosing a set of sentences as the summary, or abstractive, generating the summary from a seq2seq model. In this work, we present a neural model for single-document summarization …

Neural text summarization: A critical evaluation
W Kryscinski, NS Keskar, B McCann, C Xiong… – Proceedings of the …, 2019 – aclweb.org
Text summarization aims at compressing long documents into a shorter form that conveys the most important parts of the original document. Despite increased interest in the community and notable research effort, progress on benchmark datasets has stagnated. We …

Abstractive text summarization by incorporating reader comments
S Gao, X Chen, P Li, Z Ren, L Bing, D Zhao… – Proceedings of the AAAI …, 2019 – aaai.org
In neural abstractive summarization field, conventional sequence-to-sequence based models often suffer from summarizing the wrong aspect of the document with respect to the main aspect. To tackle this problem, we propose the task of reader-aware abstractive …

Sample efficient text summarization using a single pre-trained transformer
U Khandelwal, K Clark, D Jurafsky, L Kaiser – arXiv preprint arXiv …, 2019 – arxiv.org
Language model (LM) pre-training has resulted in impressive performance and sample efficiency on a variety of language understanding tasks. However, it remains unclear how to best use pre-trained LMs for generation tasks such as abstractive summarization …

A survey of multiple types of text summarization with their satellite contents based on swarm intelligence optimization algorithms
MA Mosa, AS Anwar, A Hamouda – Knowledge-Based Systems, 2019 – Elsevier
Due to the tremendous increment of data on the web, extracting the most important data as a conceptual brief would be valuable for certain users. Therefore, there is a massive enthusiasm concerning the generation of automatic text summary frameworks to constitute …

Query-oriented text summarization based on hypergraph transversals
H Van Lierde, TWS Chow – Information Processing & Management, 2019 – Elsevier
The rise in the amount of textual resources available on the Internet has created the need for tools of automatic document summarization. The main challenges of query-oriented extractive summarization are (1) to identify the topics of the documents and (2) to recover …

Collaborative ranking-based text summarization using a metaheuristic approach
P Verma, H Om – Emerging Technologies in Data Mining and Information …, 2019 – Springer
In the present work, a novel approach for improvement in automatic text summarization has been proposed. We introduce a different model for summarization problem by exploiting the strengths of different techniques like metaheuristic approaches and collaborative ranking …

Systematic literature review of fuzzy logic based text summarization
A Kumar, A Sharma – Iranian Journal of Fuzzy Systems, 2019 – ijfs.usb.ac.ir
Abstract Information Overload\rq is not a new term but with the massive development in technology which enables anytime, anywhere, easy and unlimited access; participation\& publishing of information has consequently escalated its impact. Assisting users\lq …

Enhancing unsupervised neural networks based text summarization with word embedding and ensemble learning
N Alami, M Meknassi, N En-nahnahi – Expert systems with applications, 2019 – Elsevier
The vast amounts of data being collected and analyzed have led to invaluable source of information, which needs to be easily handled by humans. Automatic Text Summarization (ATS) systems enable users to get the gist of information and knowledge in a short time in …

Arabic text summarization using firefly algorithm
RZ Al-Abdallah, AT Al-Taani – 2019 Amity International …, 2019 – ieeexplore.ieee.org
In this research, we propose the use of Firefly algorithm for the extraction of summaries of single Arabic documents. The proposed approach is compared with two evolutionary approaches that use genetic algorithms and harmony search. The EASC Corpus and the …

Text summarization for big data: A comprehensive survey
V Gupta, N Bansal, A Sharma – International Conference on Innovative …, 2019 – Springer
Availability of large volume of online data has necessitated the need for automatic text summarization. In this paper, a survey of various text summarization accomplishments that have been implemented in the recent past is discussed. An intentional weightage is given to …

A survey on Automatic Text Summarization
N Nazari, MA Mahdavi – Journal of AI and Data Mining, 2019 – jad.shahroodut.ac.ir
Text summarization endeavors to produce a summary version of a text, while maintaining the original ideas. The textual content on the web, in particular, is growing at an exponential rate. The ability to decipher through such massive amount of data, in order to extract the …

Neural Abstractive Text Summarization and Fake News Detection
S Esmaeilzadeh, GX Peh, A Xu – arXiv preprint arXiv:1904.00788, 2019 – arxiv.org
In this work, we study abstractive text summarization by exploring different models such as LSTM-encoder-decoder with attention, pointer-generator networks, coverage mechanisms, and transformers. Upon extensive and careful hyperparameter tuning we compare the …

DocEng’19 Competition on Extractive Text Summarization
RD Lins, RF Mello, S Simske – Proceedings of the ACM Symposium on …, 2019 – dl.acm.org
ABSTRACT The DocEng’19 Competition on Extractive Text Summarization assessed the performance of two new and fourteen previously published extractive text sumarization methods. The competitors were evaluated using the CNN-Corpus, the largest test set …

A variable dimension optimization approach for text summarization
P Verma, H Om – Harmony Search and Nature Inspired Optimization …, 2019 – Springer
Text summarization is the process of transfiguring a large document information into a clear and concise form. This paper presents a variable dimension particle swarm optimization (VDiPSO) based model for extractive text summarization. At first, the proposed model …

Leveraging BERT for extractive text summarization on lectures
D Miller – arXiv preprint arXiv:1906.04165, 2019 – arxiv.org
In the last two decades, automatic extractive text summarization on lectures has demonstrated to be a useful tool for collecting key phrases and sentences that best represent the content. However, many current approaches utilize dated approaches …

PSO-Based Text Summarization Approach Using Sentiment Analysis
S Mandal, GK Singh, A Pal – Computing, Communication and Signal …, 2019 – Springer
In the present era of technology, most of the human activities are controlled and monitored by the electronic devices and still, people are working for more advanced technology and hence to fulfill the customers requirement. Government is also promoting digitization of data …

Keyphrase generation: A text summarization struggle
E Cano, O Bojar – arXiv preprint arXiv:1904.00110, 2019 – arxiv.org
Authors’ keyphrases assigned to scientific articles are essential for recognizing content and topic aspects. Most of the proposed supervised and unsupervised methods for keyphrase generation are unable to produce terms that are valuable but do not appear in the text. In …

Global optimization under length constraint for neural text summarization
T Makino, T Iwakura, H Takamura… – Proceedings of the 57th …, 2019 – aclweb.org
We propose a global optimization method under length constraint (GOLC) for neural text summarization models. GOLC increases the probabilities of generating summaries that have high evaluation scores, ROUGE in this paper, within a desired length. We compared GOLC …

Exploring Human-Like Reading Strategy for Abstractive Text Summarization
M Yang, Q Qu, W Tu, Y Shen, Z Zhao, X Chen – Proceedings of the AAAI …, 2019 – aaai.org
The recent artificial intelligence studies have witnessed great interest in abstractive text summarization. Although remarkable progress has been made by deep neural network based methods, generating plausible and high-quality abstractive summaries remains a …

A Comprehensive Survey on Extractive and Abstractive Techniques for Text Summarization
A Mahajani, V Pandya, I Maria, D Sharma – Ambient Communications and …, 2019 – Springer
Over the years as the technology advanced, the amount of data generated during the simulations and processing has been constantly increasing. Techniques for creating synopses of this massively generated data have been in the forefront of the research in the …

Abstract Text Summarization with a Convolutional Seq2seq Model
Y Zhang, D Li, Y Wang, Y Fang, W Xiao – Applied Sciences, 2019 – mdpi.com
Abstract text summarization aims to offer a highly condensed and valuable information that expresses the main ideas of the text. Most previous researches focus on extractive models. In this work, we put forward a new generative model based on convolutional seq2seq …

A new automatic multi-document text summarization using topic modeling
RK Roul, S Mehrotra, Y Pungaliya… – International conference on …, 2019 – Springer
This paper proposes a novel methodology to generate an extractive text summary from a corpus of documents. Unlike most existing methods, our approach is designed in such a way that the final generated summary covers all the important topics from a corpus of documents …

Fuzzy rough set-based sentence similarity measure and its application to text summarization
N Chatterjee, N Yadav – IETE Technical Review, 2019 – Taylor & Francis
Fuzzy Rough Sets are designed for decision-making with uncertainty, imprecision, and incompleteness in data. We propose to use Fuzzy Rough Sets for the task of sentence similarity-based Text Summarization. Text data inherently possess uncertainty, imprecision …

Regularizing output distribution of abstractive chinese social media text summarization for improved semantic consistency
B Wei, X Ren, Y Zhang, X Cai, Q Su, X Sun – ACM Transactions on …, 2019 – dl.acm.org
Abstractive text summarization is a highly difficult problem, and the sequence-to-sequence model has shown success in improving the performance on the task. However, the generated summaries are often inconsistent with the source content in semantics. In such …

SRL-ESA-TextSum: A text summarization approach based on semantic role labeling and explicit semantic analysis
M Mohamed, M Oussalah – Information Processing & Management, 2019 – Elsevier
Automatic text summarization attempts to provide an effective solution to today’s unprecedented growth of textual data. This paper proposes an innovative graph-based text summarization framework for generic single and multi document summarization. The …

Text Summarization
T Jo – Text Mining, 2019 – Springer
This chapter is concerned with the text summarization task in terms of its function, methods, and implementation. We define the text summarization which is an instance of text mining task, in Sect. 13.1, and explore the types of text summarization, in Sect. 13.2. In Sect. 13.3, we describe …

Hierarchical summarization of text documents using topic modeling and formal concept analysis
N Akhtar, H Javed, T Ahmad – Data Management, Analytics and Innovation, 2019 – Springer
Availability of large collection of text documents triggers the need for large-scale text summarization. Identification … 839). Abstract. Availability of large collection of text documents triggers the need for large-scale text summarization …

Application of Extractive Text Summarization Algorithms to Speech-to-Text Media
DM Victor, FF Eduardo, R Biswas, E Alegre… – … Conference on Hybrid …, 2019 – Springer
This paper presents how speech-to-text summarization can be performed using extractive text summarization algorithms. Our objective is to make a recommendation about which of the six text summary algorithms evaluated in the study is the most suitable for the task of …

Text Summarization Using WordNet Graph Based Sentence Ranking
A Jain, S Vij, DK Tayal – Proceedings of 2nd International Conference on …, 2019 – Springer
Text summarization refers to the task of generating a summary from a given document that tries to replicate the most significant information of the original document. A number of techniques are available in the literature regarding the same and sentence ranking is one of …

Automatic Text Summarization For Bengali Language Including Grammatical Analysis
R Sikder, MM Hossain, F Robi – Int. J. Sci. Technol, 2019 – pdfs.semanticscholar.org
Text summarization is a process of summarize any text or document. There are many summarization tools for English language. There are also a few works for automated Bengali text or document summarization. The tools are seemed not much appropriate from …

Automatic Text Summarization of Legal Cases: A Hybrid Approach
V Pandya – arXiv preprint arXiv:1908.09119, 2019 – arxiv.org
Manual Summarization of large bodies of text involves a lot of human effort and time, especially in the legal domain. Lawyers spend a lot of time preparing legal briefs of their clients’ case files. Automatic Text summarization is a constantly evolving field of Natural …

A review on neural network based abstractive text summarization models
J Tandel, K Mistree, P Shah – 2019 IEEE 5th International …, 2019 – ieeexplore.ieee.org
Text summarization is the process to create short and concise summaries from the text document with the aim of provide most important or salient content in a condensed form from the source document. As the information is overloaded on the web, text summarization …

Key Feature Extraction and Machine Learning-Based Automatic Text Summarization
VK Verma, A Yadav, T Jain – Emerging Technologies in Data Mining and …, 2019 – Springer
Text summarization is the way to produce important sentence from the original set of sentences. Summary of text sentences can be created in many ways and means, and various methods are being developed. Automatic mechanism can create a logical summary …

Automatic Structured Text Summarization with Concept Maps
T Falke – 2019 – tuprints.ulb.tu-darmstadt.de
Efficiently exploring a collection of text documents in order to answer a complex question is a challenge that many people face. As abundant information on almost any topic is electronically available nowadays, supporting tools are needed to ensure that people can …

Attributed Rhetorical Structure Grammar for Domain Text Summarization
R Lu, S Hou, C Wang, Y Huang, C Fei… – arXiv preprint arXiv …, 2019 – arxiv.org
This paper presents a new approach of automatic text summarization which combines domain oriented text analysis (DoTA) and rhetorical structure theory (RST) in a grammar form: the attributed rhetorical structure grammar (ARSG), where the non-terminal symbols …

Multilingual Text Summarization based on LDA and Modified PageRank
S Malallah, ZH Ali – Iraqi Journal of Information Technology, 2019 – iasj.net
Text summarization is the process of generating a single document from document (s) with keeping the main idea of the summarized document (s). In this paper a proposed method which based on Linear Discriminant Analysis (LDA) and modified PageRank applied to …

Enhanced continuous and discrete multi objective particle swarm optimization for text summarization
V Priya, K Umamaheswari – Cluster Computing, 2019 – Springer
Reviews from various domains is being posted in web increasingly day by day. Analyzing this enormous content would be useful in decision making for various stakeholders. Text summarization techniques generate concise summaries including sentiments which are …

A novel approach for text summarization using optimal combination of sentence scoring methods
P Verma, H Om – S?dhan?, 2019 – Springer
In this paper, a novel multi-document summarization scheme based on metaheuristic optimization is introduced that generates a summary by extracting salient and relevant sentences from a collection of documents. The proposed work generates optimal …

Combine clustering and frequent itemsets mining to enhance biomedical text summarization
O Rouane, H Belhadef, M Bouakkaz – Expert Systems with Applications, 2019 – Elsevier
Text summarization has become an important research area, especially in the biomedical domain, where information overload is a major problem. In this paper, we propose a novel biomedical text summarization system that combines two popular data mining techniques …

Efficiency Metrics for Data-Driven Models: A Text Summarization Case Study
E Çano, O Bojar – arXiv preprint arXiv:1909.06618, 2019 – arxiv.org
Using data-driven models for solving text summarization or similar tasks has become very common in the last years. Yet most of the studies report basic accuracy scores only, and nothing is known about the ability of the proposed models to improve when trained on more …

Learning Relevant Models using Symbolic Regression for Automatic Text Summarization
E Vazquez Vazquez, Y Ledeneva… – Computación y …, 2019 – cys.cic.ipn.mx
Abstract Natural Language Processing (NLP) methods allow us to understand and manipulate natural language text or speech to do useful things. There are several specific techniques in this area, and although new approaches to solving the problems arise, its …

News Image Captioning Based on Text Summarization Using Image as Query
J Chen, H Zhuge – … on Semantics, Knowledge and Grids (SKG), 2019 – ieeexplore.ieee.org
News image captioning aims to generate captions or descriptions for news images automatically, serving as draft captions for creating news image captions manually. News image captions contain more detailed information such as entity names and events than …

Abstractive text summarization based on deep learning and semantic content generalization
P Kouris, G Alexandridis, A Stafylopatis – … of the 57th Annual Meeting of …, 2019 – aclweb.org
This work proposes a novel framework for enhancing abstractive text summarization based on the combination of deep learning techniques along with semantic data transformations. Initially, a theoretical model for semantic-based text generalization is introduced and used in …

SummAE: Zero-shot abstractive text summarization using length-agnostic auto-encoders
PJ Liu, YA Chung, J Ren – arXiv preprint arXiv:1910.00998, 2019 – arxiv.org
We propose an end-to-end neural model for zero-shot abstractive text summarization of paragraphs, and introduce a benchmark task, ROCSumm, based on ROCStories, a subset for which we collected human summaries. In this task, five-sentence stories (paragraphs) are …

Combining text summarization and aspect-based sentiment analysis of users’ reviews to justify recommendations
C Musto, G Rossiello, M de Gemmis, P Lops… – Proceedings of the 13th …, 2019 – dl.acm.org
In this paper we present a methodology to justify recommendations that relies on the information extracted from users’ reviews discussing the available items. The intuition behind the approach is to conceive the justification as a summary of the most relevant and …

A hybrid classification-based model for automatic text summarisation using machine learning approaches: CBS-ID3MV
ME Hannah – International Journal of Product Development, 2019 – inderscienceonline.com
A hybrid approach for the generation of automatic text summarisation is achieved through CBS-ID3MV. A classification-based model using ID3 and multivariate (CBS-ID3MV) approach produces summaries from the text documents through classification and multiple …

Speech to text conversion and summarization for effective understanding and documentation
A Vinnarasu, DV Jose – International Journal of Electrical and …, 2019 – search.proquest.com
… Text summarization extracts the utmost important information from a source which is a text and provides the adequate summary of the same … Keywords: Feature extraction Natural language processing Natural language toolkit Speech recognition Text summarization …

LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization
T Shi, P Wang, CK Reddy – arXiv preprint arXiv:1906.01512, 2019 – arxiv.org
Neural abstractive text summarization (NATS) has received a lot of attention in the past few years from both industry and academia. In this paper, we introduce an open-source toolkit, namely LeafNATS, for training and evaluation of different sequence-to-sequence based …

The CNN-Corpus in Spanish: a Large Corpus for Extractive Text Summarization in the Spanish Language
RD Lins, H Oliveira, L Cabral, J Batista… – Proceedings of the …, 2019 – dl.acm.org
This paper details the development and features of the CNN-corpus in Spanish, possibly the largest test corpus for single document extractive text summarization in the Spanish language. Its current version encompasses 1,117 well-written texts in Spanish, each of them …

Error tolerant global search incorporated with deep learning algorithm to automatic Hindi text summarisation
J Anitha, PP Reddy, MSP Babu – International Journal of …, 2019 – inderscienceonline.com
There is an exponential growth in the available electronic information in the last two decades. It causes a huge necessity to quickly understand high volume text data. This paper describes an efficient algorithm and it works by assigning scores to sentences in the …

Learning with fuzzy hypergraphs: a topical approach to query-oriented text summarization
H Van Lierde, TWS Chow – Information Sciences, 2019 – Elsevier
Existing graph-based methods for extractive document summarization represent sentences of a corpus as the nodes of a graph in which edges depict relationships of lexical similarity between sentences. This approach fails to capture semantic similarities between sentences …

Social media based event summarization by user–text–image co-clustering
X Qian, M Li, Y Ren, S Jiang – Knowledge-Based Systems, 2019 – Elsevier
JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …

Individual differences in main idea identification and text summarization in EFL reading comprehension: an exploratory study
GVV Prebianca – Leitura, 2019 – seer.ufal.br
Abstract: This expioratory smaii-scaie study investigates EFL learners’ abiiity to read in a foreign ianguage, particuiarly their main idea identification and text summarization skiils as products of their reading comprehension processes. Four pre-intermedíate students, ciassified as good …

An efficient single document Arabic text summarization using a combination of statistical and semantic features
A Qaroush, IA Farha, W Ghanem, M Washaha… – Journal of King Saud …, 2019 – Elsevier
The exponential growth of online textual data triggered the crucial need for an effective and powerful tool that automatically provides the desired content in a summarized form while preserving core information. In this paper, we propose an automatic, generic, and extractive …

Analysis of Competitor Intelligence in the Era of Big Data: An Integrated System Using Text Summarization Based on Global Optimization
S Chakraborti, S Dey – Business & Information Systems Engineering, 2019 – Springer
Automatic text summarization can be applied to extract summaries from competitor intelligence (CI) corpora that organizations create by gathering textual data from the Internet. Such a representation of CI text is easier for managers to interpret and use for making …

Experiment with Text Summarization as a Positive Hierarchical Fuzzy Logic Ranking Indicator for Domain Specific Retrieval of Malay Translated Hadith
SB bin Rodzman, NK Ismail… – 2019 IEEE 9th …, 2019 – ieeexplore.ieee.org
Ranking function acts as a predictive algorithm that is used to establish a simple ordering of documents according to its relevance and this process shows the effectiveness, quality and the accuracy for the variety type of Information Retrieval (IR) such as, Domain Specific …

Gist: general integrated summarization of text and reviews
J Lovinger, I Valova, C Clough – Soft Computing, 2019 – Springer
… Gist is a modular text summarization framework … Rather than attempting to create a catch-all system, we design Gist to allow changes within the existing system while focusing on core features that are essential for text summarization …

A Strategical Review on Text Summarization
P Kumar, K Sharma – Research & Reviews: A …, 2019 – computerjournals.stmjournals.in
Text summarization is the important component of the document analysis. Reading the complete set of documents if the work is tedious, so that the summary presents the brief idea about the whole document. In this paper we review the concept of the automatic text …

Text Summarization using Word Frequency
VJ Yadav, TM Pandey, HM Rathore, AR Pandey – ijisrt.com
In today’s world, where lot of information is accessible on the Internet, it is of utmost importance to provide a better method to retrieve fast and accurate information. We face a lot of difficulty for extracting the brief information about a large document of text. On the internet …

Automatic text summarization
A Shamprasad, AG Krishna, BM Shashank, J Reshma… – 2019 – pdfs.semanticscholar.org
In the recent years we have seen an increasing amount of data generation in every field. It becomes our utmost priority to manage this data. The data produced can be structured or unstructured. When it comes to gain knowledge through data, it becomes easier if we only …

Performance Analysis of Extractive Text Summarization
V Patel – 2019 – thescholarship.ecu.edu
In this era, data is increasing exponentially, and it is crucial for people to keep up with all of this information. The information is available in several different forms such as news articles, online blogs, etc., many of which may be too long to read by an individual in order to gain …

Text Summarization
C Room – Architecture, 2019 – devopedia.org
On the web, everyone can be a publisher. We’re already seeing vast amounts of information being published daily in the form of restaurant/movie/book reviews, blogs, status updates, and more. In addition, traditional print publications (newspapers, magazines, technical …

Extractive Text Summarization Using Sentence Ranking
JN Madhuri, RG Kumar – 2019 International Conference on …, 2019 – ieeexplore.ieee.org
Automatic Text summarization is the technique to identify the most useful and necessary information in a text. It has two approaches 1) Abstractive text summarization and 2) Extractive text summarization. An extractive text summarization means an important …

Extractive Text Summarization Methods: A Review
A Goel, P Goyal – ijaconline.com
In recent years, there has been an explosion in the amount of text data from a variety of sources. This has made it important to provide a mechanism to extract the information rapidly and efficiently. Manually extracting the summary of a large number of documents …

Automatic Text Summarization System
R Deepa, J Konshi, A Haritha, K Shobini – ripublication.com
Text mining or text analytics is the process of deriving high-quality information from text. It is challenging for users to go through the entire content available on the internet. Text summarization is part of text mining. Text summarization methods are greatly needed to …

Idiap Abstract Text Summarization System for German Text Summarization Task
S Parida, P Motlicek – Proceedings of the 4th edition of the …, 2019 – pdfs.semanticscholar.org
Text summarization is considered as a challenging task in the NLP community. The availability of datasets for the task of multilingual text summarization is rare, and such datasets are difficult to construct. In this work, we build an abstract text summarizer for the …

Text summarization using multiobjective optimization
S Saha – CSI Transactions on ICT, 2019 – Springer
In this article, I have briefly described one of my research areas namely text summarization. The problem definition, state of the art techniques and some preliminary results are presented. There are different types of summarization systems available like document …

Reinforcement Learning Models for Abstractive Text Summarization
S Buciumas – Proceedings of the 2019 ACM Southeast Conference, 2019 – dl.acm.org
Abstractive text summarization is an active research topic in Natural Language Understanding. We live in a digital world where the information for every topic in Internet is increasing considerable, and users would benefit by generating summaries. Summaries are …

Abstractive Text Summarization
R Nallapati, B Zhou, C dos Santos, Ç Gulçehre… – aisc.ai.science
Page 1. Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond Written by: Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, Çaglar Gulçehre, and Bing Xiang From IBM and Université de Montréal Presented by: Ehsan Amjadian @RBC Page 2. Summary • …

Text Categorization with Text Summarization Techniques
PVP Reddy – pramanaresearch.org
This paper addresses the issue of curse of dimensionality in the Text Classification (TC) problem using Text Summarization (TS). In this paper, an attempt is made to effectively tackle the curse of dimensionality problem using Text classification model. It is observed …

Marathi text summarization using Neural Networks
A Chaudhari, A Dole, D Kadam – International Journal for Advance …, 2019 – ijarnd.com
The internet is comprised of web pages, news articles, status updates, blogs and much more. It is difficult to navigate through this data as it is unstructured and usually discursive. Condensed versions of this data are generated so we can navigate it more effectively as …

Hybrid Text Summarization: A Survey
M Kirmani, NM Hakak, M Mohd, M Mohd – Soft Computing: Theories and …, 2019 – Springer
Text summarization is the technique of shirking the original text document in such a way that its meaning is not altered. Summarization techniques have become important for information retrieval as large volumes of data are available on Internet and it is impossible for a human …

Text Summarization and Generation in Social Media
S PECAR, M SIMKO – rebelion.fiit.stuba.sk
Social media contains plethora of user-generated text, which can be considered as an important source of information. While the amount of user-generated content will still grow, we will not be able to effectively seek information within it. This can lead to the problems with …

Text Summarization: An Essential Study
P Janjanam, CHP Reddy – 2019 International Conference on …, 2019 – ieeexplore.ieee.org
The proliferation of data from diverse sources makes humans insufficient in utilizing the knowledge properly at some instance. To quickly have an overview of abundant information, Text Summarization (TS) comes into play. TS will effectively extract the candidate sentences …

A New Technique for Extrinsic Text Summarization
N Kindo, G Bhuyan, R Padhy – Computing and Network Sustainability, 2019 – Springer
Text summarization is the process where a text document is downsized, with a computer program, so as to create a summarized text and possesses the most essential points of the primary text. The present work is one new type of extrinsic technique of summarization …

A Survey on Automatic Text Summarization Methods
J Chadha – 2019 – academia.edu
In today’s world wealth of data is available o Internet, text mining plays a vital role in many fields. Text mining has been widely used as 80%(approx..) of the data is unstructured. Mining information from voluminous data is a tedious job. Automatic text summarization is a …

Text Summarization using Neural Networks
A Jadhav, R Jain, S Fernandes… – … on Advances in …, 2019 – ieeexplore.ieee.org
Text Summarization is the technique of extricating notable data from the first content archive. In this procedure, the separated data is produced as a consolidated report and introduced as a clearly expressed rundown. Text Summarization can be broadly classified into …

Text Summarization for Natural Language based on Text Ranking
N Garg, T Jain – ijisrt.com
Within recent times, there has been a need for text summary generators to cut short lengthy academic or non-academic texts for effective reading. In recent times, there have been many techniques that deploy text summarization yet, their speed, efficiency and scalability is a …

Abstractive Text Summarization Using Artificial Intelligence
C Parmar, R Chaubey, K Bhatt… – … Conference on Advances …, 2019 – papers.ssrn.com
Text summarization is the process of creating concise summary of text. There are two main approaches to summarization namely extractive and abstractive method. Most of the system summaries use extractive method. Amongst few abstractive models available there are two …

Text Summarization for Chatbots
M Lustig – 2019 – support.dce.felk.cvut.cz
Guidelines: Text summarization is a natural language processing task of producing a shorter version of a document that preserves most of the original document’s meaning while staying grammatically correct. The aim of this work is to incorporate a selected method into a …

Personality-dependent Neural Text Summarization
P Costa, I Paraboni – Proceedings of the International Conference on …, 2019 – aclweb.org
Abstract In Natural Language Generation systems, personalization strategies-ie, the use of information about a target author to generate text that (more) closely resembles human-produced language-have long been applied to improve results. The present work addresses …

Text Summarization of Product Titles
J Xiao, R Munro – 2019 – ceur-ws.org
In this work, we investigate the problem of summarizing titles of e-commerce products. With the increase in popularity of voice shopping due to smart phones and (especially) in-home speech devices, it is necessary to shorten long text-based titles to more succinct titles that …

An Automatic Text Summarization: A Systematic
V Patel, N Tabrizi – 2019 – wvvw.easychair.org
The 21st century has become a century of information overload, where in fact information related to even one topic (due to its huge volume) takes a lot of time to manually summarize it into few lines. Thus, in order to address this problem, Automatic Text Summarization …

A Detail Survey on Automatic Text Summarization
RS Sajjan, MG Shinde – 2019 – researchgate.net
the document summarization is becoming essential as lots of information getting generated every day. Instead of going through the entire text document, it is easy to understand the text document fast and easily by a relevant summary. Text summarization is the method of …

An Attention-Based Approach to Text Summarization
R Panchal, A Pagarkar, L Kurup – … of the 2nd International Conference on …, 2019 – Springer
Text summarization has become increasingly important in today’s world of information overload. Recently, simpler networks using only attention mechanisms have been tried out for neural machine translation. We propose to use a similar model to carry out the task of text …

Attention Based Models for Text Summarization
K Sen, R Dev, SM Jayant, U Doley – 2019 – sml.csa.iisc.ernet.in
Page 1. E0-270 Machine Learning Attention Based Models for Text Summarization Date:27-04-2019 Koushik Sen Rahul Dev Shah Manan Jayant Upasana Doley Page 2. INTRODUCTION • Text summarization means creating a smaller version of original text that …

Text Summarization in the Biomedical Domain
M Moradi, N Ghadiri – arXiv preprint arXiv:1908.02285, 2019 – arxiv.org
This chapter gives an overview of recent advances in the field of biomedical text summarization. Different types of challenges are introduced, and methods are discussed concerning the type of challenge that they address. Biomedical literature summarization is …

Japanese abstractive text summarization using BERT
Y Iwasaki, A Yamashita, Y Konno… – … on Technologies and …, 2019 – ieeexplore.ieee.org
In this study, we developed an automatic abstractive text summarization algorithm in Japanese using a neural network. We used a sequence-to-sequence encoder-decoder model for experimentation purposes. The encoder obtained a feature-based input vector of …

Deep learning approach for Malagasy text summarization
VM Ratianantitra, JL Razafindramintsa, T Mahatody… – wairco.org
In this paper, we deal automatic text summarization in Malagasy language. Malagasy is the national language of Madagascar. Several techniques have been developed to summarize texts in English and other European languages etc. But few research works has been done …

An Extractive Approach for English Text Summarization
KD Patil, SA Patil, YS Deshmukh – ijsar.in
Natural-language processing (NLP) is a vast area of computer science, artificial intelligence concerned with the interactions between computers and human languages. The “natural language” means a language that is used for daily communication by humans. The …

Kazakh Text Summarization using Fuzzy logic
A Zulkhazhav, Z Kozhirbayev… – Computación y …, 2019 – cys.cic.ipn.mx
In this paper we present an extractive summarization method for the Kazakh language based on fuzzy logic. We aimed to extract and concatenate important sentences from the primary text to obtain its shorter form. With the rapid growth of information on the Internet …

Abstractive Text Summarization Using Enhanced Attention Model
RK Roul, PM Joshi, JK Sahoo – International Conference on Intelligent …, 2019 – Springer
Text summarization is the technique for generating a concise and precise summary of voluminous texts while focusing on the sections that convey useful information, and without losing the overall meaning. Although recent works are paying attentions in this domain, but …

Improving Abstractive Text Summarization with History Aggregation
P Liao, C Zhang, X Chen, X Zhou – arXiv preprint arXiv:1912.11046, 2019 – arxiv.org
Recent neural sequence to sequence models have provided feasible solutions for abstractive summarization. However, such models are still hard to tackle long text dependency in the summarization task. A high-quality summarization system usually …

Corpora and Evaluation for Text Summarisation
P Mehta, P Majumder – From Extractive to Abstractive Summarization: A …, 2019 – Springer
A standard benchmark collection is essential to the reproducibility of any research. Several initial works in text summarisation suffered due to lack of standard evaluation corpora at that time [1, 8]. The advent of conferences like Document Understanding Conference (DUC)[2] …

Aspect-Based Text Summarization Using MapReduce Optimization
V Priya, K Umamaheswari – Computational Intelligence and Sustainable …, 2019 – Springer
Aspect-based summarization techniques require improvement in accuracy of the generated summaries. These systems show significant role in the analysis of web review contents. Also they are useful to analyse the reviews in the web which increases drastically day by day. So …

Text Summarization in Indian Languages: A Critical Review
N Baruah, SK Sarma… – 2019 Second International …, 2019 – ieeexplore.ieee.org
Everyday the internet is flooded with huge volume of data. This huge volume of text data is undeniably a valuable source of knowledge but at the same time it is not feasible for web users to go through all the information or data available due to time constraint. Thus …

Distance Based Image Text Extraction And Summarization Approach
V Sharma, R Sharma – ijtre.com
… Vikas Sharma 1 , Rahul Sharma 2 1 M. Tech Scholor, 2 Assistant Professor, Sri Balaji College of Engineering and Technology Jaipur Rajasthan Abstract: Text Summarization means making the layout of the account … Keywords : Text Summarization, Image Text Extraction …

Seminar Neural Text Summarization
J Steen – 2019 – cl.uni-heidelberg.de
This document is a preliminary schedule for the seminar and subject to change based on the number of students and their interests. To complete the course you need to participate regularly (no more than one unexcused absence) and be active in the discussions. Each …

A Bengali Text Generation Approach in Context of Abstractive Text Summarization using RNN
AKM Masum – researchgate.net
Automatic text summarization is one of the mentionable research area of natural language processing. The amount of data is increasing rapidly as well the necessity of understanding the gist of any text is just a mandatory tools, now a days. The area of text summarization has …

Relevance Vector Machine Optimization in Automatic Text Summarization
KE Dewi, E Rainarli – IOP Conference Series: Materials Science …, 2019 – iopscience.iop.org
This study aims at optimizing the Relevance Vector Machine (RVM) algorithm in automatic text summarization. This research begins by studying various studies on automatic text summarization to find out what features are commonly used in the automatic text …

A Semantic Text Summarization Model for Arabic Topic-Oriented
RM Badry, IF Moawad – … on Advanced Machine Learning Technologies and …, 2019 – Springer
In the era of data overloading, Text Summarization systems (TSs) is one of the important Natural Language processing applications. These systems provide a concise form for the input document (s). According to the type of output summary, Text Summarization can be …

Text Summarization Techniques Survey on Telugu and Foreign Languages
S Shashikanth, S Sanghavi – ijresm.com
Text summarization is the process of reducing a text document and creating a summary. Summaries are two types. Abstractive and Extractive summaries. An Extractive summary involve extracting relevant sentences from the source text in proper order. Abstractive …

Two-Level Text Summarization with Natural Language Processing
R Hande, A Sidhwani, D Sidhwani, M Shiv… – … on Computer Networks …, 2019 – Springer
Text summarization is the process of shortening a text document in order to create a summary covering important points, aspects of the original document. Text summarization methods are based on extractive model and abstractive model. Two-level text …

Analysing Fuzzy Based Approach for Extractive Text Summarization
A Sharaff, AS Khaire, D Sharma – … International Conference on …, 2019 – ieeexplore.ieee.org
In today’s era of information, there is gigantic amount of data available from various sources. Not only does the enormous volumes pose problems, searching of required information becomes a very difficult task. It is the need of the hour to have smaller but significant …

Text Summarization and Topic Models
D Sarkar – Text Analytics with Python, 2019 – Springer
We have come quite a long way in our journey through the world of text analytics and natural language processing. You have seen how to process and annotate textual data for various applications. We also looked at state-of-the-art text representation methods with feature …

Sentence Similarity Measurement for Bengali Abstractive Text Summarization
AKM Masum, S Abujar, RTH Tusher… – 2019 10th …, 2019 – ieeexplore.ieee.org
Text summarization is a massive research area in natural language processing. It reduces the larger text and provided the prime meaning of a text document. Find the meaning of the larger text needed of a proper text analysis which gives a better text summarizer. Abstractive …

Wajeez: An Extractive Automatic Arabic Text Summarisation System
A Al Oudah, K Al Bassam, H Kurdi… – … Conference on Human …, 2019 – Springer
The volume of Arabic information is rapidly increasingly nowadays, and thus, access to the corrects is arguably one of the most difficult research problems facing readers and researchers. Text Summarisation Systems are utilised to produce a short text describing …

Abstract Text Summarization: A Low Resource Challenge
S Parida, P Motlicek – Proceedings of the 2019 Conference on Empirical …, 2019 – aclweb.org
Text summarization is considered as a challenging task in the NLP community. The availability of datasets for the task of multilingual text summarization is rare, and such datasets are difficult to construct. In this work, we build an abstract text summarizer for the …

Cross-Lingual Korean Speech-to-Text Summarization
HJ Yoon, DT Hoang, NT Nguyen, D Hwang – Asian Conference on …, 2019 – Springer
The development of a cross-lingual text summarization of a language differing from that of the source document has been a challenge in recent years. This paper describes a summarization system built to auto-translate Korean speech into an English summary text …

Extractive Odia Text Summarization System: An OCR Based Approach
P Pattnaik, DK Mallick, S Parida, SR Dash – International Conference on …, 2019 – Springer
Automatic text summarization is considered as a challenging task in natural language processing field. In the case of multilingual scenario particularly for the low-resource, morphologically complex languages the availability of summarization data set is rare and …

Word Embedding-Based Biomedical Text Summarization
O Rouane, H Belhadef, M Bouakkaz – International Conference of Reliable …, 2019 – Springer
In this paper, we have proposed a novel word embedding-based biomedical text summarizer. Biomedical words are represented by real dense vectors. Sentences are represented by summing-up the word vectors that contain. The PageRank algorithm is …

Highlighted Word Encoding for Abstractive Text Summarization
DM Lal, KP Singh, US Tiwary – International Conference on Intelligent …, 2019 – Springer
The proposed model unites the robustness of the extractive and abstractive summarization strategies. Three tasks indispensable to automatic summarization, namely, apprehension, extraction, and abstraction, are performed by two specially designed networks, the …

Ranking-Based Sentence Retrieval for Text Summarization
A Mahajani, V Pandya, I Maria, D Sharma – Smart Innovations in …, 2019 – Springer
Text summarization is the technique of extricating notable data from the first content archive. In this procedure, the separated data is produced as a consolidated report and introduced as a clearly expressed rundown. Extractive summarization technique includes choosing …

Graph-Based Fuzzy Logic for Extractive Text Summarization (GFLES)
MR Alfarra, AM Alfarra, JM Alattar – … International Conference on …, 2019 – ieeexplore.ieee.org
High accuracy models for automatic text summarization are increasingly required due to the overwhelming growth of available text on the internet. In this paper, a new unsupervised approach for Automatic Text Summarization (ATS) employing Fuzzy Logic (FL) to optimize …

Extractive Text Summarization-An effective approach to extract information from Text
AR Mishra, VK Panchal, P Kumar – … International Conference on …, 2019 – ieeexplore.ieee.org
Everyday large volume of data is gathered from different sources and are stored since they contain valuable piece of information. The storage of data must be done in efficient manner since it leads in difficulty during retrieval. Text data are available in the form of large …

Automatic text summarization of Swedish news articles
N Lehto, M Sjödin – 2019 – diva-portal.org
With an increasing amount of textual information available there is also an increased need to make this information more accessible. Our paper describes a modified TextRank model and investigates the different methods available to use automatic text summarization as a …

A Survey Paper On Question Pair Similarity and Text Summarization
DY Chakke, NK Rajput, RR Rege, PR Jaiswal – vjer.in
With the proliferation of internetbased data, the information sought by relevant researchers can overlap over multiple data sources. To avoid this redundancy and to make the process of researching easier, platforms which render similar question grouping and assist in …

Unsupervised Method for Text Summarization Using Content Based Approach
R Jain – Available at SSRN 3356308, 2019 – papers.ssrn.com
In this era Internet has surprising growth in terms of availability of documents. It gave a rise to exhaustive research in the field of Automatic Text Summarization. The text that is extracted from one or more textual contents and is no longer than half of the original text is called as …

Abstractive Text Summarization with Multi-Head Attention
J Li, C Zhang, X Chen, Y Cao, P Liao… – … Joint Conference on …, 2019 – ieeexplore.ieee.org
In this paper, we present a novel sequence-to-sequence architecture with multi-head attention for automatic summarization of long text. Summaries generated by previous abstractive methods have the problems of duplicate and missing original information …

Convolutional Neural Network based for Automatic Text Summarization
WH Alquliti, NBA Ghani – researchgate.net
In recent times, the apps for the processing of a natural language has been formed and generated through the use of intelligent and soft computing methods that allow computer systems to practically mimic practices related to the process of human texts like the detection …

Cutting Down “Fluff” A Twist on Text Summarization
GT da Silva, K Salmon – cs230.stanford.edu
In this paper we explore the task of making text concise, which we define as keeping all ideas of a text intact in as few words as possible. We built a dataset of 2,225 pairs mapping cluttered text to their concise version, which we used to train our constructed extractive …

Extractive Approach For Query Based Text Summarization
GVM Chandu, A Premkumar… – … Conference on Issues …, 2019 – ieeexplore.ieee.org
The last few years have seen a tremendous surge in the information that is being dumped online. In this digital world every organization have their respective website which gives a detailed knowledge about them to the public. Considering organizations like educational …

A Hybrid Approach for Multi-document Text Summarization
R Varma – 2019 – scholarworks.sjsu.edu
Text summarization has been a long studied topic in the field of natural language processing. There have been various approaches for both extractive text summarization as well as abstractive text summarization. Summarizing texts for a single document is a …

Automatic Text Summarization of Chinese Legal Information
D Lande, Z Yang, S Zhu, J Guo, M Wei – academia.edu
Article is devoted to a method of automatic text summarization of the legal information provided in Chinese. The structure of the abstract and the model of its formation is considered. Two approaches are suggested. First one is determination of weight of separate …

Enhancing a Text Summarization System with ELMo
C Mastronardo, F Tamburini – 2019 – ceur-ws.org
Text summarization has gained a considerable amount of research interest due to deep learning based techniques. We leverage recent results in transfer learning for Natural Language Processing (NLP) using pre-trained deep contextualized word embeddings in a …

Automatic Arabic Text Summarization Based on Fuzzy Logic
L Al Qassem, D Wang, H Barada, A Al-Rubaie… – Proceedings of the 3rd …, 2019 – aclweb.org
The unprecedented growth in the amount of online information available in many languages to users and businesses, including news articles and social media, has made it difficult and time consuming for users to identify and consume sought after content. Hence, automatic …

Coverage-Based Variational Generative Decoder for Abstractive Text Summarization
X Huang, W Teng, J Lin, Y Bao – 2019 IEEE 4th Advanced …, 2019 – ieeexplore.ieee.org
Neural abstractive summarization models, based on the attentional sequence-to-sequence model, can generate simple summarization from source text. However, these models inevitably face with repetition problem, and ignore the rich structure information contained in …

Automatic Text Summarization using Natural Language Processing
S Behal, A Gupta, VK Sehgal – 2019 – ir.juit.ac.in
Automatic text summarization is basically summarizing of the given paragraph using natural language processing and machine learning. There has been an explosion in the amount of text data from a variety of sources. This volume of text is an invaluable source of information …

A Novel Approach of Text Summarization using Assamese WordNet
N Baruah, SK Sarma… – 2019 4th International …, 2019 – ieeexplore.ieee.org
Automatic Text Summarization techniques in Assamese language is still in an immature stage compared to other Indian languages. In this study, we have reviewed some of the studies in other Indian languages for having a better understanding of the problems …

Text Summarization using Partial Textual Entailment based Graphs
M Kaur, D Srivastava – … on Machine Learning, Big Data, Cloud …, 2019 – ieeexplore.ieee.org
Information explosion has boosted research communities to propose many text summarization methods using different approaches. Text connectedness is a potential textual attribute to identify significant sentences from the source document to form a …

Text Summarization Model of Combining Global Gated Unit and Copy Mechanism
S Ren, K Guo – 2019 IEEE 10th International Conference on …, 2019 – ieeexplore.ieee.org
Text summarization is a common task in NLP. Automatic text summarization aims to transform lengthy documents into shortened versions. Recently, the neural networks based on seq2seq with attention are good at generating summarization. However, the accuracy of …

Neural Text Summarization: A Critical Evaluation
W Kry?ci?ski, NS Keskar, B McCann, C Xiong… – arXiv preprint arXiv …, 2019 – arxiv.org
Text summarization aims at compressing long documents into a shorter form that conveys the most important parts of the original document. Despite increased interest in the community and notable research effort, progress on benchmark datasets has stagnated. We …

Text Summarization Using Adaptive Neuro-Fuzzy Inference System
PD Warule, SD Sawarkar, A Gulati – Computing and Network Sustainability, 2019 – Springer
Nowadays, data present on the World Wide Web is growing exponentially. People use search engines like Google, Bing, and Yahoo for retrieving the required information. But as the information present on the Web is huge, it is necessary for user to make the summary of …

Extractive Arabic Text Summarization Using Modified PageRank Algorithm
R Elbarougy, G Behery, A El Khatib – Egyptian Informatics Journal, 2019 – Elsevier
This paper proposed an approach for Arabic text summarization. Text summarization is one of the natural language processing’s applications which is used for reducing the original text amount and retrieving only the important information from the original text. The Arabic …

A Comparison Of Automatic Extractive Text Summarization Techniques
A Day, S Kim – 34th Annual Conference of The Pennsylvania …, 2019 – cs.millersville.edu
Text summarization is a method of shortening a document by producing a set of representative information. It can be generally categorized into extractive and abstractive summarization. Extractive summarization-the focus of this paper-is extracting sentences and …

Application and analysis of text summarization for biomedical domain content
K Ouyang – cs229.stanford.edu
Biomedical information in the form of scientific articles and electronic medical records is increasing at an alarmingly fast pace. The output of publications in the biomedical domain is estimated to double every 5-10 years, currently with more than 3000 new articles published …

Hybrid Latent Semantic Analysis and Random Indexing Model for Text Summarization
N Chatterjee, N Yadav – Information and Communication Technology for …, 2019 – Springer
Latent semantic analysis has been used successfully for extractive text summarization for years, while random indexing-based summarization has been recently proposed in the literature for text summarization. The random indexing-based summarization inherently uses …

An Approach for Bengali Text Summarization using Word2Vector
S Abujar, AKM Masum, M Mohibullah… – 2019 10th …, 2019 – ieeexplore.ieee.org
Text Summarization is one of the mentionable research areas of Natural language processing. Several approaches have already been developed in this concern. Such as-Abstractive approach and extractive approach. Most recent recurrent neural network …

Knowledge-guided Unsupervised Rhetorical Parsing for Text Summarization
S Hou, R Lu – arXiv preprint arXiv:1910.05915, 2019 – arxiv.org
Automatic text summarization (ATS) has recently achieved impressive performance thanks to recent advances in deep learning and the availability of large-scale corpora. To make the summarization results more faithful, this paper presents an unsupervised approach that …

Principled Approaches to Automatic Text Summarization
M Peyrard – 2019 – tuprints.ulb.tu-darmstadt.de
Automatic text summarization is a particularly challenging Natural Language Processing (NLP) task involving natural language understanding, content selection and natural language generation. In this thesis, we concentrate on the content selection aspect, the …

Text Summarization in Social Networks by using Deep Learning
E Do?an, B Kaya – 2019 1st International Informatics and …, 2019 – ieeexplore.ieee.org
Social networks are user-based platforms where users share their thoughts and feelings visually or in writing. Social networks are also networks where users can comment on the topic (s). Emotion analysis and text summarization on shared data and big data in social …

Keyphrase Guided Beam Search for Neural Abstractive Text Summarization
X Chen, J Li, H Wang – 2019 International Joint Conference on …, 2019 – ieeexplore.ieee.org
As a recently proposed way of text summarization, abstractive text summarization features the use of new phrases to obtain a condensed version of the source text. Most approaches nowadays in this category are under the sequence-to-sequence framework, which is the …

A Multi-Task Learning Framework for Abstractive Text Summarization
Y Lu, L Liu, Z Jiang, M Yang, R Goebel – … of the AAAI Conference on Artificial …, 2019 – aaai.org
We propose a Multi-task learning approach for Abstractive Text Summarization (MATS), motivated by the fact that humans have no difficulty performing such task because they have the capabilities of multiple domains. Specifically, MATS consists of three components:(i) a …

Exploring Domain Shift in Extractive Text Summarization
D Wang, P Liu, M Zhong, J Fu, X Qiu… – arXiv preprint arXiv …, 2019 – arxiv.org
Although domain shift has been well explored in many NLP applications, it still has received little attention in the domain of extractive text summarization. As a result, the model is under-utilizing the nature of the training data due to ignoring the difference in the distribution of …

TextRank enhanced Topic Model for Query focussed Text Summarization
N Akhtar, MMS Beg, H Javed – 2019 Twelfth International …, 2019 – ieeexplore.ieee.org
Topic model based query focused text summarization methods can meet the user’s needs as they are able to find subtopics and their correlations. Topic model based summarization method does not score the sentences directly as they generates topics distributions, which …

Extending The Performance of Extractive Text Summarization By Ensemble Techniques
A Bharadwaj, A Srinivasan, A Kasi… – 2019 11th International …, 2019 – ieeexplore.ieee.org
Text summarization techniques help in automatically shortening the length of text data as well as fluently and accurately passing on the intended message. Extractive Text summarization methods have been well-researched but each such algorithm produces a …

Sequence Generative Adversarial Network for Chinese Social Media Text Summarization
W Yang, R Hua, Q Zhao – 2019 Chinese Automation Congress …, 2019 – ieeexplore.ieee.org
Although the sequence-to-sequence models have achieved state-of-the-art performance in many summarization datasets, there are still some problems in the processing of Chinese social media text, such as short sentences, lack of coherence and accuracy. These issues …

Multi-Document Extractive Text Summarization via Deep Learning Approach
A Rezaei, S Dami, P Daneshjoo – 2019 5th Conference on Knowledge … – ieeexplore.ieee.org
Today, given the huge amount of information, summarization has become one of the most applicable topics in data mining that can help users gain access to useful data over a short period of time. In this study, two multi-document extractive text Summarization systems are …

Performance Analysis of Frequency and Graph Theoretic Based Text Summarization
PC Karmaker, MS Hossen – 2019 International Conference on …, 2019 – ieeexplore.ieee.org
Nowadays people are becoming busy with their office and family activities. They do not get enough time to study the newspaper completely. But they need to update themselves to the events of the current world. Hence, text summarization can help them to know the events …

Passage-Based Text Summarization for Legal Information Retrieval
A Kanapala, S Jannu, R Pamula – Arabian Journal for Science and …, 2019 – Springer
Automatic text summarization is a process of condensing the content of a text document to pursue the most important information. It plays a significant role in various tasks like text categorization, question answering and information retrieval (IR). As legal information …

Automatic Text Summarization of News Articles in Serbian Language
D Kosmajac, V Kešelj – 2019 18th International Symposium …, 2019 – ieeexplore.ieee.org
Text Summarization is a technique of creating short, accurate, and fluent summaries of longer text documents or sets of documents. With growing amount of textual data circulating in the digital space, there is a need to develop machine learning algorithms that can …

A Reinforced Improved Attention Model for Abstractive Text Summarization
YCHLX Li, Y Huang – 2019 – waseda.repo.nii.ac.jp
In recent times, RNN-based sequence-tosequence attentional models have achieved good performance on abstractive summarization. However, numerous problems regarding repetition, incoherence, and exposure bias are encountered when applying these models. In …

Abstractive Multi-Document Text Summarization Using a Genetic Algorithm
RA García-Hernández – … MCPR 2019, Querétaro, Mexico, June 26 …, 2019 – books.google.com
Multi-Document Text Summarization (MDTS) consists of generating an abstract from a group of two or more number of documents that represent only the most important information of all documents. Generally, the objective is to obtain the main idea of several documents on the …

Automating TL; DR: An Approach to Text Summarization
H Han – 2019 – haomiaohan.com
Computers and technology have had a profound influence on how information spread in today’s society–increasingly, people prefer to read news and acquire other types of new information online, rather than using traditional ways such as reading newspapers or books …

Automatic Text Summarization Based on Transformer and Switchable Normalization
T Luo, K Guo, H Guo – 2019 IEEE Intl Conf on Parallel & …, 2019 – ieeexplore.ieee.org
With the development of text summarization research, the methods based on RNN with the Encoder-Decoder model gradually become the mainstream. However, RNN tends to forget previous context information and leads to the lack of original information. That will reduce …

Unsupervised Text Summarization via Mixed Model Back-Translation
Y Jernite – arXiv preprint arXiv:1908.08566, 2019 – arxiv.org
Back-translation based approaches have recently lead to significant progress in unsupervised sequence-to-sequence tasks such as machine translation or style transfer. In this work, we extend the paradigm to the problem of learning a sentence summarization …

Sequential transfer learning in NLP for text summarization
P Fecht – inovex.de
This thesis investigates recent techniques for transfer learning and their influence on machine summarization systems. A current trend in Natural Language Processing (NLP) is to pre-train extensive language models in advance and adapt these to address problems in …

A Supervised Approach For Extractive Text Summarization Using Minimal Robust Features
D Krishnan, P Bharathy… – … on Intelligent Computing …, 2019 – ieeexplore.ieee.org
Over the past decade or so the amount of data on the Internet has increased exponentially. Thus arises the need for a system that processes this immense amount of data into useful information that can be easily understood by the human brain. Text summarization is one …

A Study on Relevance Measure with Compression Ratio for Text Summarization
PVP Reddy – pramanaresearch.org
Text summarization (TS) is a process condensing the original text into shorter form by retaining the actual content of the text. This paper addresses the process of generating the summary for a given Telugu text document using Maximal Marginal Relevance (MMR) …

Extractive Text Summarization Using Ontology and Graph-Based Method
C Yongkiatpanich, D Wichadakul – 2019 IEEE 4th International …, 2019 – ieeexplore.ieee.org
In recent years, many people started to take care of the physical health. The biomedical article is the trendy issue at the moment leading to the huge amount of knowledge created rapidly. In this paper, we propose a new automatic extractive text summarization technique …

NLP: Text Summarization By Frequency And Sentence Position Methods
NK Raja, N Bakala, S Suresh – pdfs.semanticscholar.org
In today’s fast-growing online information age we have an abundance of text, especially on the web. New information is constantly being generated. Often due to time constraints we are not able to consume all the data available. It is therefore essential to be able to …

Extractive Text Summarization Technique Using Fuzzy C-Means Clustering Algorithm
J Uddin, MI Mobin – 2019 International Conference on …, 2019 – ieeexplore.ieee.org
Text summarization process has become one of the significant research areas for years owing to cope up with the astounding increase of virtual textual materials. Text summarization is the process to keep the relevant important information of the original text in …

Ontology-based Extractive Text Summarization: The Contribution of Instances
ML Flores, ER Santos, RA Silveira – Computación y Sistemas, 2019 – cys.cic.ipn.mx
In this paper, we present a text summarization approach focusing on multi-document, extractive and query-focused summarization that relies on an ontology-based semantic similarity measure, that specifically explores ontology instances. We employ the DBpedia …

Extractive Text Summarization using Deep Natural Language Fuzzy Processing
G Neelima, MRM Veeramanickam… – researchgate.net
Text summarization is most trending research areas in a modern context. The main aim of this project is to reduce text size while preserving the information underlying into it. In summary construction level, in general, given complex task which are basically will involve …

Multi Document Text Summarization Using Machine Learning
VN Hemnani, MK Prasad, SAS Aland, B Vyas – eprajournals.com
Summarization process is always needs more precision and time to yield the best results. This is due to the vastness of the data, complexities in the narration of the documents and constrained time boundaries. So the task of Document summary extraction is always full of …

Sequential Transfer Learning in NLP for German Text Summarization
P Fecht, S Blank, HP Zorn – 2019 – ceur-ws.org
This work examines the impact of sequential transfer learning on abstractive machine summarization. A current trend in Natural Language Processing (NLP) is to pre-train extensive language models and then adapt these models to solve various target tasks …

Towards Supervised Extractive Text Summarization via RNN-based Sequence Classification
E Brito, M Lübbering, D Biesner, LP Hillebrand… – arXiv preprint arXiv …, 2019 – arxiv.org
This article briefly explains our submitted approach to the DocEng’19 competition on extractive summarization. We implemented a recurrent neural network based model that learns to classify whether an article’s sentence belongs to the corresponding extractive …

K-Means and K-Medoids for Indonesian Text Summarization
KK Purnamasari – IOP Conference Series: Materials Science and …, 2019 – iopscience.iop.org
The purpose of this study is to build automated summation tools, especially in grouping methods such as K-Means and K-Medoids. Finding the best method between the two algorithms, this study focuses on comparing the two methods to summarize thesis report …

Literature Review of Automatic Text Summarization: Research Trend, Dataset and Method
AP Widyassari, A Affandy… – … on Information and …, 2019 – ieeexplore.ieee.org
Automatic text summarization can be defined as the process of presenting one or more text documents while maintaining the main information content using an automatic machine with no more than half the original text or less than the original text. Research in the field of text …

Deep Learning Based Extractive Text Summarization: Approaches, Datasets and Evaluation Measures
D Suleiman, AA Awajan – 2019 Sixth International Conference …, 2019 – ieeexplore.ieee.org
Recently, the number of online documents witness huge increase in volume. Thus, these documents need to be summarized in order to be effective. This paper reviews the most recent extractive text summarization approaches that are based on deep learning …

Facet-Aware Evaluation for Extractive Text Summarization
Y Mao, L Liu, Q Zhu, X Ren, J Han – arXiv preprint arXiv:1908.10383, 2019 – arxiv.org
Commonly adopted metrics for extractive text summarization like ROUGE focus on the lexical similarity and are facet-agnostic. In this paper, we present a facet-aware evaluation procedure for better assessment of the information coverage in extracted summaries while …

Deep Architectures for Abstractive Text Summarization in Multiple Languages
AM Zaki, MI Khalil, HM Abbas – 2019 14th International …, 2019 – ieeexplore.ieee.org
Abstractive text summarization is the task of generating a novel summary given an article, not by merely extracting and selecting text to produce a summary, but by actually creating and understating the given text to produce a summary. LSTM seq2seq encoder-decoder …

Abstractive Multi-Document Text Summarization Using a Genetic Algorithm
VN Mendoza, Y Ledeneva… – Mexican Conference on …, 2019 – Springer
Abstract Multi-Document Text Summarization (MDTS) consists of generating an abstract from a group of two or more number of documents that represent only the most important information of all documents. Generally, the objective is to obtain the main idea of several …

A Study on Implementation of Text Summarization Techniques on Indian Languages
PV Reddy – adalyajournal.com
Automatic text summarization is to compress an original document into an abridged version by extracting almost all of the essential concepts with text mining techniques. This research focuses on developing a hybrid automatic text summarization approach to enhancing the …

Building an Extractive Arabic Text Summarization Using a Hybrid Approach
SM Lakhdar, MA Chéragui – International Conference on Arabic Language …, 2019 – Springer
Nowadays, textual information in numerical format is hugely produced, which requires the development of tools such as Automatic Text Summarization to produce a condensed and relevant representation, thus helping the reader to decide whether the source document …

Towards German Abstractive Text Summarization using Deep Learning
K von Luck – users.informatik.haw-hamburg.de
Text summarization is an established sequence learning problem divided into extractive and abstractive models. While extractive models learn to only rank words and sentences, abstractive models learn to generate language as well. The great success of deep learning …

Semantic based Automatic Text Summarization based on Soft Computing
J Chadha – 2019 – academia.edu
Automated Summarizer is a tool which extracts lines from a text file and generates a brief information in a proper manner. Even though many approaches have been developed, some important aspects of summaries, such as grammar, responsiveness are still evaluated …

Mind The Facts: Knowledge-Boosted Coherent Abstractive Text Summarization
B Gunel, C Zhu, M Zeng, X Huang – pdfs.semanticscholar.org
Neural models have become successful at producing abstractive summaries that are human-readable and fluent. However, these models have two critical shortcomings: they often don’t respect the facts that are either included in the source article or are known to humans as …

Indonesian Abstractive Text Summarization Using Bidirectional Gated Recurrent Unit
R Adelia, S Suyanto, UN Wisesty – Procedia Computer Science, 2019 – Elsevier
Abstractive text summarization is more challenging than the extractive one since it is performed by paraphrasing the entire contents of the text, which has a higher difficulty. But, it produces a more natural summary and higher inter-sentence cohesion. Recurrent Neural …

Automatic Keyword Detection for Text Summarization
RS Koka – 2019 – uh-ir.tdl.org
Lecture videos are extremely useful and great learning companions for students. The ICS (Indexed, Captioned, and Searchable) video project provides students a flexible way to navigate across the lectures by automatically dividing the lecture into topical segments …

Optimization of Text Summarization Based on Feature Selection and Classification
K Gowri, RM Chezian – pdfs.semanticscholar.org
Understanding the contents of a document via a text summarized version of the document requires a shorter time than reading the entire document, so that the summary text becomes very important. summarization requires a lot of time and cost when the documents are …

CS224N Project Report Faster Transformers for Text Summarization
A Sabran, A Matton – pdfs.semanticscholar.org
A recently proposed neural network architecture called the Transformer [1] works very well for many NLP tasks. However, its runtime is quadratic in the length of the input sequence, which means it can be slow when processing long documents or taking characters as inputs …

Extractive based Text Summarization Using K-Means and TF-IDF
R Khan, Y Qian, S Naeem – International Journal of Information …, 2019 – mecs-press.net
The quantity of information on the internet is massively increasing and gigantic volume of data with numerous compositions accessible openly online become more widespread. It is challenging nowadays for a user to extract the information efficiently and smoothly. As one of …

A Shortcut-Stacked Document Encoder for Extractive Text Summarization
P Yan, L Li, D Zeng – 2019 International Joint Conference on …, 2019 – ieeexplore.ieee.org
While doing summarization, human needs to understand the whole document, rather than separately understanding each sentence in the document. However, inter-sentence features within one document are not adequately modeled by previous neural network-based models …

Improving Transformer with Sequential Context Representations for Abstractive Text Summarization
T Cai, M Shen, H Peng, L Jiang, Q Dai – CCF International Conference on …, 2019 – Springer
Recent dominant approaches for abstractive text summarization are mainly RNN-based encoder-decoder framework, these methods usually suffer from the poor semantic representations for long sequences. In this paper, we propose a new abstractive …

An Automatic Text Summarization on Naive Bayes Classifier Using Latent Semantic Analysis
C Shah, A Jivani – Data, Engineering and Applications, 2019 – Springer
Currently, huge information is available on Internet, but it is difficult to find the relevant information at a fast and efficient rate. Large collection of textual data is available on the Internet. A very competent system is required to find the most appropriate information from …

Cross-Task Knowledge Transfer for Query-Based Text Summarization
E Egonmwan, V Castelli, MA Sultan – … of the 2nd Workshop on Machine …, 2019 – aclweb.org
We demonstrate the viability of knowledge transfer between two related tasks: machine reading comprehension (MRC) and query-based text summarization. Using an MRC model trained on the SQuAD1. 1 dataset as a core system component, we first build an extractive …

The Impact of Local Attention in LSTM for Abstractive Text Summarization
PM Hanunggul, S Suyanto – 2019 International Seminar on …, 2019 – ieeexplore.ieee.org
An attentional mechanism is very important to enhance a neural machine translation (NMT). There are two classes of attentions: global and local attentions. This paper focuses on comparing the impact of the local attention in Long Short-Term Memory (LSTM) model to …

Improvement of query-based text summarization using word sense disambiguation
N Rahman, B Borah – Complex & Intelligent Systems, 2019 – Springer
In this paper, a query-based text summarization method is proposed based on common sense knowledge and word sense disambiguation. Common sense knowledge is integrated here by expanding the query terms. It helps in extracting main sentences from text document …

Research on Automatic Text Summarization Method Based on TF-IDF
T Zhang, C Chen – International Conference on Intelligent and Interactive …, 2019 – Springer
In order to quickly obtain the main information contained in news documents, reduce redundant information and improve the efficiency of finding news with specific content. A Chinese text summarization method based on TF-IDF is proposed. This method uses TF-IDF …

An efficient Approach for Text Summarization using Latent Semantic Analysis
TE Ramya, N Magesh – jicrjournal.com
Text summarization aims at getting the most significant content in a system of condensed form from a given document while it retains the semantic information of the text to a large extent. It is considered to be an effective way of tackling information overload. It solves the …

Bengali Text Summarization using TextRank, Fuzzy C-Means and Aggregate Scoring methods
A Rahman, FM Rafiq, R Saha… – 2019 IEEE Region 10 …, 2019 – ieeexplore.ieee.org
In this world, it is very difficult and time consuming for humans to summarize large documents, reports, news and research articles. Multiple text summarization techniques play vital roles in picking the important points and sentences thus reducing the time and effort …

Extractive Text Summarization Using Graph Based Ranking Algorithm And Mean Shift Clustering
R Ramesh, B Rajan – Available at SSRN 3439357, 2019 – papers.ssrn.com
Text summarization is the process of converting a huge text file into a summarized version preserving its meaning and context. The major aspect of any extractive text summarization technique is to provide precise and accurate summary by using any sentence ranking …

SumSAT: Hybrid Arabic Text Summarization based on symbolic and numerical Approaches
MA Cheragui, SM Lakhdar – … of the 3rd International Conference on …, 2019 – aclweb.org
The increase in number and volume of electronic documents makes the development of applications such as text summarization crucial, in order to facilitate the task for persons who want to consult their documents. The purpose of an electronic document summary is the …

Abstractive Text Summarization using Peephole Convolutional LSTM
MM Rahman – 2019 – duet.ac.bd
Abstractive text summarization is a process of making a summary of a given text by paraphrasing the facts of the text while keeping the meaning intact. Most of the abstractive text summarization is based on traditional LSTM that has some limitations such as it does …

A Comparative Analysis on Hindi and English Extractive Text Summarization
P Verma, S Pal, H Om – ACM Transactions on Asian and Low-Resource …, 2019 – dl.acm.org
Text summarization is the process of transfiguring a large documental information into a clear and concise form. In this article, we present a detailed comparative study of various extractive methods for automatic text summarization on Hindi and English text datasets of …

Evaluation of the Transformer Model for Abstractive Text Summarization
F Jonsson – 2019 – diva-portal.org
Being able to generate summaries automatically could speed up the spread and retention of information and potentially increase productivity in several fields. Using RNN-based encoder-decoder models with attention have been successful on a variety of language …

A Novel Attention Mechanism Considering Decoder Input for Abstractive Text Summarization
J Niu, M Sun, JJPC Rodrigues… – ICC 2019-2019 IEEE …, 2019 – ieeexplore.ieee.org
Recently, the automatic text summarization has been widely used in text compression tasks. The Attention mechanism is one of the most popular methods used in the seq2seq (Sequence to Sequence) text summarization models. The current attention mechanisms …

Discourse-Aware Neural Extractive Model for Text Summarization
J Xu, Z Gan, Y Cheng, J Liu – arXiv preprint arXiv:1910.14142, 2019 – arxiv.org
Recently BERT has been adopted in state-of-the-art text summarization models for document encoding. However, such BERT-based extractive models use the sentence as the minimal selection unit, which often results in redundant or uninformative phrases in the …

Pointer-Generator Abstractive Text Summarization Model with Part of Speech Features
S Ren, Z Zhang – 2019 IEEE 10th International Conference on …, 2019 – ieeexplore.ieee.org
The typical sequence-to-sequence with attention mechanism models have achieved good results in the task of abstractive text summarization. However, this kind of models always have some shortcomings: they have out-of-vocabulary (OOV) problems, sometimes may …

Saliency Maps Generation for Automatic Text Summarization
D Tuckey, K Broda, A Russo – arXiv preprint arXiv:1907.05664, 2019 – arxiv.org
Saliency map generation techniques are at the forefront of explainable AI literature for a broad range of machine learning applications. Our goal is to question the limits of these approaches on more complex tasks. In this paper we apply Layer-Wise Relevance …

Abstractive method of text summarization with sequence to sequence RNNs
AKM Masum, S Abujar, MAI Talukder… – 2019 10th …, 2019 – ieeexplore.ieee.org
Text summarization is one of the famous problems in natural language processing and deep learning in recent years. Generally, text summarization contains a short note on a large text document. Our main purpose is to create a short, fluent and understandable abstractive …

Streamlined Slide Generation by Performing Extractive Text Summarization
L Nithyanandham, A Madduri, S Sainadh Makineni… – pdfs.semanticscholar.org
Power Point Presentations have long been used by people to display information in an easy and eye-catching manner. Many organizations use the PowerPoint Presentations for discussing their projects with stakeholders, or for their project reviews. Many students use …

Automatic Evaluation of Text Summarization Based on Semantic Link Network
M Cao, H Zhuge – … on Semantics, Knowledge and Grids (SKG), 2019 – ieeexplore.ieee.org
This paper proposes an approach for automatically evaluating summaries based on Semantic Link Network (SLN). Three factors about the quality of summary are taken into account: 1) Fidelity, inspecting whether a summary conveys the core themes of the source …

Improving Accuracy of Key Information Acquisition for Social Media Text Summarization
W Miao, G Zhang, Y Bai, D Cai – 2019 IEEE International …, 2019 – ieeexplore.ieee.org
The attention-based sequence-to-sequence (Seq2Seq) model for abstractive summarization has achieved good performance, but it still suffers from generating inaccurate information and repetitive content when applied to noisy social media text. To address these issues, we …

The Enhancement of Arabic Information Retrieval Using Arabic Text Summarization
A Ababneh – 2019 – eprints.hud.ac.uk
The massive upload of text on the internet makes the text overhead one of the important challenges faces the Information Retrieval (IR) system. The purpose of this research is to maintain reasonable relevancy and increase the efficiency of the information retrieval …

VIKOR Algorithm Based on Cuckoo Search for Multi-document Text Summarization
ZH Ali, AA Noor, MA Jassim – … on Applied Computing to Support Industry …, 2019 – Springer
Due to the huge amount of documents on the internet and the redundancy contained in each document makes it difficult for the user to get useful information. Automatic text summarization is a solution to such problems of information overload. Text summarization is …

The method of multidimensional approach to text summarization
P Janaszkiewicz, P Ró?ewski – Procedia Computer Science, 2019 – Elsevier
Nowadays, the amount of different type of data for analysis is growing at an alarming rate. Moreover, the size and quantity of textual materials make the extraction of specific information from them more and more complicated and sometimes impossible. The use of …

Evaluating the Factual Consistency of Abstractive Text Summarization
W Kry?ci?ski, B McCann, C Xiong, R Socher – arXiv preprint arXiv …, 2019 – arxiv.org
Currently used metrics for assessing summarization algorithms do not account for whether summaries are factually consistent with source documents. We propose a weakly-supervised, model-based approach for verifying factual consistency and identifying conflicts …

Multi-document extractive text summarization: A comparative assessment on features
B Mutlu, EA Sezer, MA Akcayol – Knowledge-Based Systems, 2019 – Elsevier
Text summarization is the process of generating a brief version of a text that preserves the salient information of the text. For information retrieval, it is a good dimension reduction solution. In addition, it reduces the required reading time. This study focused on extracting …

A topic-based sentence representation for extractive text summarization
N Gialitsis, N Pittaras, P Stamatopoulos – Proceedings of the Workshop …, 2019 – aclweb.org
In this study, we examine the effect of probabilistic topic model-based word representations, on sentence-based extractive summarization. We formulate the task of summary extraction as a binary classification problem, and we test a variety of machine learning algorithms …

Abstractive Text Summarization On Wikihow Dataset Using Sentence Embeddings
B TOZYILMAZ – 2019 – etd.lib.metu.edu.tr
Summarization is a well known natural language processing task that is used in our day-to-day lives. The field saw recent research using neural networks and word embeddings. We use WikiHow dataset and show that we can match performance of a similar model using …

A Sequence-to-Sequence Text Summarization Model with Topic Based Attention Mechanism
HX Pan, H Liu, Y Tang – … Conference on Web Information Systems and …, 2019 – Springer
One of the limitation of automatic summarization is that how to take into account and reflect the implicit information conveyed between different text and the scene influence. In particularly, the generation of news headlines should under specific scene and topic in the …

An idea based on sequential pattern mining and deep learning for text summarization
DS Maylawati, YJ Kumar, FB Kasmin… – Journal of Physics …, 2019 – iopscience.iop.org
Abstract One of the Natural Language Processing (NLP) studies that has been widely researched is automatic text summarization. There are a lot of techniques and methods that are proposed for text summarization. However, not much attention has been given on the …

Text summarization using transfer learnin: Extractive and abstractive summarization using BERT and GPT-2 on news and podcast data
V RISNE, A SIITOVA – 2019 – odr.chalmers.se
A summary of a long text document enables people to easily grasp the information of the topic without having the need to read the whole document. This thesis aims to automate text summarization by using two approaches: extractive and abstractive. The former approach …

Abstractive Text Summarization of Research Articles Based on Word Associations
G Dineshnath, S Saraswathi – Journal of Computational and …, 2019 – ingentaconnect.com
Research articles need to be summarized based on the user requirement to foster research activity. Summarization system should provide either extractive or abstractive summary based on the contextual information pertaining in articles. Summarizer prevailing now is …

Summarization of Odia Text Document Using Cosine Similarity and Clustering
S Pattnaik, AK Nayak – 2019 International Conference on …, 2019 – ieeexplore.ieee.org
… Abstract— Automatic text summarization a subfield of Natural Language Processing (NLP) aims at producing precise and non redundant text aided by machine learning techniques … in the area of Automatic text summarization is covered in this section …

eStep: A Novel Method for Semantic Text Summarization with Web-based Big Data
S Das – pdfs.semanticscholar.org
Text summarization plays an important role in analysis of large set of data. It can be use in online text analysis and knowledge representation. Semantic text summarization plays a vital role to handle big data as data is in very large size, dynamic in nature and …

VAE-PGN based Abstractive Model in Multi-stage Architecture for Text Summarization
H Choi, L Ravuru, T Dryjanski, S Rye, D Lee… – Proceedings of the 12th …, 2019 – aclweb.org
This paper describes our submission to the TL; DR challenge. Neural abstractive summarization models have been successful in generating fluent and consistent summaries with advancements like the copy (Pointer-generator) and coverage mechanisms. However …

Extractive Text Summarization Techniques of News Articles: Issues, Challenges and Approaches
S Singh, A Singh, S Majumder… – … on Vision Towards …, 2019 – ieeexplore.ieee.org
With the burst of information on the Web, there is a need to compress without eliminating facts and index for further reference highlighting the need for automatic text summarization techniques. With the increasing social and occupational requisites, humans need to process …

The effect of noise in the training of convolutional neural networks for text summarisation
A Meechan-Maddon – 2019 – diva-portal.org
In this thesis, we work towards bridging the gap between two distinct areas: noisy text handling and text summarisation. The overall goal of the paper is to examine the effects of noise in the training of convolutional neural networks for text summarisation, with a view to …

Abstractive Text Summarization Using Pointer-Generator Networks With Pre-trained Word Embedding
DT Anh, NTT Trang – Proceedings of the Tenth International Symposium …, 2019 – dl.acm.org
Abstractive text summarization is the task of generating a summary that captures the main content of a text document. As a state-of-the-art method for abstractive summarization, the pointer-generator network produces more fluent summaries and solves two shortcomings of …

Development of a Konkani Language Dataset for Automatic Text Summarization and its Challenges
J D’Silva, U Sharma – ripublication.com
Text summarization has gained tremendous popularity in the research field over the last few years. Automatic Text summarization attempts to automate the summarization task, which would otherwise, be done by humans. Research has progressed a lot in the said domain in …

A Review Paper on Comparison of Different Algorithm Used in Text Summarization
S Basak, MDDH Gazi, SMMH Chowdhury – International Conference on …, 2019 – Springer
At present, Data remains as the most important part of human life. The future of data generation is manipulated through different data analysis techniques. But every day it is becoming much more difficult. Due to current growth of technology, People are generating …

A Novel Algorithm for Automatic Text Summarization System Using Lexical Chain
A Tiwari, D Dembla – Ambient Communications and Computer Systems, 2019 – Springer
In the field of text classification and information retrieval, the process of text summarization has always been an important aspect. It decreases the size of text and preserves its information content by providing a shorter illustration. This illustration has the major portion …

Survey of Progressive Era of Text Summarization for Indian and Foreign Languages Using Natural Language Processing
AD Dhawale, SB Kulkarni, V Kumbhakarna – International Conference on …, 2019 – Springer
The last few years of Data Science definitely show the upward trend in growth of popularity, different industries which are effectively relating with data science & the transformation of world with e-commerce sites, social networking sites, travel aggregators, Google assistants …

Deep Learning Based Sentiment Analysis and Text Summarization in Social Networks
E Do?an, B Kaya – 2019 International Artificial Intelligence and …, 2019 – ieeexplore.ieee.org
Sentiment analysis aims to reveal semantic knowledge of written texts where users share their feelings and thoughts on sharing platforms such as personal blogs and social networks. The data shared by users on social networks consist of short texts. A text …

Employing neural hierarchical model with pointer generator networks for abstractive text summarization
W Chowdhury – 2019 – summit.sfu.ca
As the growth of online data continues, automatic summarization is integral in generating a condensed version of a text while preserving the meaning of the original input. Although most of the earlier works on automatic summarization use extractive approaches to identify …

A framework for extractive text summarization using semantic graph based approach
S Ullah, ABMAA Islam – Proceedings of the 6th International Conference …, 2019 – dl.acm.org
Automatic extractive text summarization finds the subset of the data, which represent the most salient information of the entire document. Now-a-days in the era of Internet, it is a demand of the users to understand the huge amount of texts within a very short time, as …

A Systematic and Exhaustive Review of Automatic Abstrac-tive Text Summarization for Hindi Language
A Garg, JR Saini – researchgate.net
Text summarization is the process of extracting salient information from the source text and to present that information to the user in the form of summary. It is very difficult for human beings to manually summarize large documents of text. Automatic abstractive summarization …

An Optimized Abstractive Text Summarization Model Using Peephole Convolutional LSTM
M Rahman, FH Siddiqui – Symmetry, 2019 – mdpi.com
Abstractive text summarization that generates a summary by paraphrasing a long text remains an open significant problem for natural language processing. In this paper, we present an abstractive text summarization model, multi-layered attentional peephole …

Automatic Text Summarization Based on Semantic Networks and Corpus Statistics
W Yulita, S Priyanta, SN Azhari – IJCCS (Indonesian Journal of … – journal.ugm.ac.id
One simple automatic text summarization method that can minimize redundancy, in summary, is the Maximum Marginal Relevance (MMR) method. The MMR method has the disadvantage of having parts that are separated from each other in summary results that are …

Towards automatic extractive text summarization of A-133 Single Audit reports with machine learning
VT Chou, LA Kent, JA Góngora, S Ballerini… – arXiv preprint arXiv …, 2019 – arxiv.org
The rapid growth of text data has motivated the development of machine-learning based automatic text summarization strategies that concisely capture the essential ideas in a larger text. This study aimed to devise an extractive summarization method for A-133 Single Audits …

Text Image Extraction and Summarization
N Joshi – Asian Journal For Convergence In Technology (AJCT), 2019 – asianssr.org
… Language Toolkit. [3] Information extraction and text summarization using linguistic knowledge acquisition.- The lack of extensive linguistic coverage is the major barrier to extracting useful information from large bodies of text. Current …

Text Summarisation Using Laplacian Centrality-Based Minimum Vertex Cover
A Gupta, M Kaur – Journal of Information & Knowledge Management, 2019 – World Scientific
Outdegree Centrality (OC) is a graph-based centrality measure that captures local connectedness of a node in a graph. The measure has been used in the literature to highlight key sentences in a graph-based optimisation method for summarisation. It is …

Indonesian Automatic Text Summarization Based on A New Clustering Method in Sentence Level
Z Cai, N Lin, C Ma, S Jiang – … of the 2019 International Conference on Big …, 2019 – dl.acm.org
With the development of the Internet, the amount of information grows exponentially, and the automatic text summarization technology becomes more and more important. At present, the majority of researches on automatic summarization techniques are applied to common …

An Improved Attention Layer assisted Recurrent Convolutional Neural Network Model for Abstractive Text Summarization
D Nagalavi, M Hanumanthappa… – INFOCOMP Journal of …, 2019 – dcc.ufla.br
In the last few years text summarization has gained widespread attention across industries, especially in media and publications, research, business intelligence etc where it helps exploiting large documents to generate a new one with summarized inferences without …

Automated Text Summarization for the Enhancement of Public Services
X Liu, J Jumadinova – arXiv preprint arXiv:1910.10490, 2019 – arxiv.org
Natural language processing and machine learning algorithms have been shown to be effective in a variety of applications. In this work, we contribute to the area of AI adoption in the public sector. We present an automated system that was used to process textual …

Rough sets based span and its application to extractive text summarization
N Yadav, N Chatterjee – Journal of Intelligent & Fuzzy Systems, 2019 – content.iospress.com
Rough Sets provide a mathematical tool to handle decision making under uncertainty. One major domain that can be characterized with inherent ambiguity is natural language texts which often leads to uncertainty in understanding the intent and relative importance of a …

An Investigation on Peer Assessment: Teaching Text Summarization in English
NV Guskova – Journal of History Culture and Art Research, 2019 – 193.140.9.50
Özet This paper discusses the specifics of using the method of peer assessment in the process of learning a brief text summary in English by the students of non-linguistic specialties. In particular, the effectiveness and expediency of using peer assessment in …

Parallelizing a multi-objective optimization approach for extractive multi-document text summarization
JM Sanchez-Gomez, MA Vega-Rodríguez… – Journal of Parallel and …, 2019 – Elsevier
Currently, automatic multi-document text summarization is an important task in many fields of knowledge, due to the continuous exponential growth of information on the Internet. Nevertheless, this task is computationally demanding. In the last years, automatic text …

Automatic text summarization: What has been done and what has to be done
A Aries, WK Hidouci – arXiv preprint arXiv:1904.00688, 2019 – arxiv.org
Summaries are important when it comes to process huge amounts of information. Their most important benefit is saving time, which we do not have much nowadays. Therefore, a summary must be short, representative and readable. Generating summaries automatically …

Supplementary Material for EMNLP 2019 Paper: Text Summarization with Pretrained Encoders
Y Liu, M Lapata – nlp-yang.github.io
Ablation studies are conducted to show the contribution of different components of BERTSUM. The results are shown in Table 1. Under extractive setting, interval segments and the intersentence Transformer layers increase the performance of base model. Under …

Towards neural abstractive clinical trial text summarization with sequence to sequence models
C Cintas, W Ogallo, A Walcott, SL Remy… – 2019 IEEE …, 2019 – ieeexplore.ieee.org
The recruitment stage in clinical trials is key in ensuring enrollment of a large and diverse number of participants. Recent trends in clinical trials recruitment strategies have leveraged social media, mobile, and web-based platforms to advertise trials to a broader and more …

A Formal Technique for Text Summarization from Web Pages by using Latent Semantic Analysis
JG Ramos, I Navarro-Alatorre, GF Becerra… – … in Computing Science, 2019 – rcs.cic.ipn.mx
Web is the more attractive media for information consulting of, practically, whatever theme; humanity considers the Web, in the facts, the standard source of information. However as content grows, effort for discriminating and filtering increases too. Orthogonally, users …

Improving Latent Alignment in Text Summarization by Generalizing the Pointer Generator
X Shen, Y Zhao, H Su, D Klakow – … of the 2019 Conference on Empirical …, 2019 – aclweb.org
Pointer Generators have been the de facto standard for modern summarization systems. However, this architecture faces two major drawbacks: Firstly, the pointer is limited to copying the exact words while ignoring possible inflections or abstractions, which restricts its …

Domain specific concept ontologies and text summarization as hierarchical fuzzy logic ranking indicator on malay text corpus
SB bin Rodzman, NK Ismail… – Indonesian Journal of …, 2019 – researchgate.net
Ranking function is a predictive algorithm that is used to establish a simple ordering of documents according to its relevance. This step is critical because the results’ quality of a Domain Specific Information Retrieval (IR) such as Hadith Information Retrieval is …

Performance Evaluation of Manhattan and Euclidean Distance Measures For Clustering Based Automatic Text Summarization
SA Salihu, IP Onyekwere, MA Mabayoje… – FUOYE Journal of …, 2019 – researchgate.net
In the past few years, there has been an explosion in the amount of text data from a variety of sources. This volume of text is a valuable source of information and knowledge which needs to be effectively summarized to be useful. In this paper, automatic text summarization with K …

Speech to text conversion and summarization for effective understanding and documentation.
DV Jose – International Journal of Electrical & Computer …, 2019 – search.ebscohost.com
… Text summarization extracts the utmost important information from a source which is a text and provides the adequate summary of the same … Keywords: Feature extraction Natural language processing Natural language toolkit Speech recognition Text summarization …

A nifty review to text summarization-based recommendation system for electronic products
RK Roul, K Arora – Soft Computing, 2019 – Springer
With the commencement of new technology, demands of online shopping are increasing day by day and hence an electronic product receives a huge number of customers reviews everyday. Because of this, a customer who wants to buy a particular product face difficulty as …

Extractive Text Summarization Methods Inspired By Reinforcement Learning for Better Generalization Master Thesis
Y Virin – 2019 – pdfs.semanticscholar.org
This master thesis opens with a description of several text summarization methods based on machine learning approaches inspired by reinforcement learning. While in many cases Maximum Likelihood Estimation (MLE) approaches work well for text summarization, they …

Integration Distance Similarity with Keyword Algorithm for Improving Cohesion between Sentences in Text Summarization
R Darmawan, A Wijaya – IOP Conference Series: Materials …, 2019 – iopscience.iop.org
In recent time the exponential growth of textual information available on the Web, end user need to be able to access information in summary form. Commonly the method to get the summary is extraction method. One of extraction method that easier and commonly used is …

Extraction-Based Text Summarization and Sentiment Analysis of Online Reviews Using Hybrid Classification Method
N Yadav, R Kumar, B Gour… – … Conference on Wireless …, 2019 – ieeexplore.ieee.org
The field of sentiment mining and text summarization has evoked the interest of many scientists and researchers over the last few years, as the textual data has become useful for many real-world applications and challenges. Sentiment Analysis and Opinion Mining is the …

Implementation of Chinese Reader Aid for Visually-Impaired by Using Neural Network and Text Summarization Technologies
LJ Chen, CY Chen, HY Chen… – … on Machine Learning …, 2019 – ieeexplore.ieee.org
This paper proposes the intelligent system to assist the visually-impaired people in reading printed Chinese document. As the document may consist of the combination of text and photos, the proposed system first applies the text frame detection scheme to identify the text …

Automating Text Summarization With Machine Learning: Extraction of End Results From Result Reports
M Ahlsén, C Edberg, M Larsson – 2019 – diva-portal.org
The Swedish International Development Cooperation Agency (SIDA) handles the financial aid Sweden gives to parter organisations for devel-opment activities. When an activity has ended, the partner organizations write reports on what they accomplished and how the grant …

Natural Language Justifications for Recommender Systems Exploiting Text Summarization and Sentiment Analysis
C Musto, G Rossiello, M de Gemmis, P Lops… – 2019 – ceur-ws.org
This paper reports and summarizes the methodology presented in [16] and accepted for publication at ACM RecSys 2019 1. In this work we present a methodology to justify recommendations that relies on the information extracted from users’ reviews discussing the …

Automatic text summarisation of case law using gate with annie and summa plug-ins
CT Aghaunor, GO Ekuobase – Nigerian Journal of Technology, 2019 – ajol.info
Legal reasoning and judicial verdicts in many legal systems are highly dependent on case law. The ever increasing number of case law make the task of comprehending case law in a legal case cumbersome for legal practitioners; and this invariably stifles their efficiency …

Automatic Text Summarization: A New Hybrid Model Based on Vector Space Modelling, Fuzzy Logic and Rhetorical Structure Analysis
AB Ayed, I Biskri, JG Meunier – International Conference on Computational …, 2019 – Springer
In this paper, we present a new hybrid system for automatic text summarization. First, vector space modelling is used to compute two original metrics of coverage and fidelity. The latter metrics are combined onto a unified Fidelity-Coverage (FC) score using fuzzy logic theory …

Towards Adaptive Text Summarization: How Does Compression Rate Affect Summary Readability of L2 Texts?
T Vodolazova, E Lloret – Proceedings of the International Conference on …, 2019 – aclweb.org
This paper addresses the problem of readability of automatically generated summaries in the context of second language learning. For this we experimented with a new corpus of level-annotated simplified English texts. The texts were summarized using a total of 7 …

Automatic text summarisation using an advanced stemmer algorithm: a case study of the Xhosa Language
Z Ndyalivana, Z Shibeshi – Educor Multidisciplinary Journal, 2019 – journals.co.za
In today’s world, digital content is becoming significantly abundant. Finding ways to come up with a tool that can aid with this is of fundamental importance. People are faced with what is referred to as information overload. A tool that can make a summary of a text without losing …

Domain Category Information as a Guide for Sentence Ranking to Support Medical Text Summarization
KE Maduabunachukwu – 2019 – atrium2.lib.uoguelph.ca
Medical professionals are required to pursue evidence-based practice by including the best available evidence from published research in their decision-making process. However, the exponential growth of biomedical resources makes it difficult for them to follow this …

ISUTD: Intelligent System for Urdu Text De-Summarization
MW Bhatti, M Aslam – 2019 International Conference on …, 2019 – ieeexplore.ieee.org
… In general arguments, the summary can explain as the discovery of conclusion and noiseless features from the briefly defined documents [2]. Text summarization (TS) is one of the dynamic strengths of many scientific areas …

An Improved Text Summarization Using Feature Selection And Optimized Naive Bayes Classification Compared With Latent …
K Gowri, RM Chezian – pdfs.semanticscholar.org
Perceptive the contents of a document via a text summarized version of the document needs a shorter time than reading the complete document, so the outline text becomes important. Report needs a great deal of your time and price once the documents square measure …

Comparison of automatic methods for reducing the Pareto front to a single solution applied to multi-document text summarization
JM Sanchez-Gomez, MA Vega-Rodríguez… – Knowledge-Based …, 2019 – Elsevier
Nowadays, automatic text summarization methods are needed in many different contexts. Extractive multi-document summarization approaches are intended to, simultaneously, synthesize the main content of a document collection and reduce the redundant information …

Toward an automatic summarisation of Arabic text depending on rhetorical relations
S Lagrini, N Azizi, M Redjimi… – International Journal of …, 2019 – inderscienceonline.com
… Related Content Search. Find related content. By Keyword: rhetorical relations; Arabic language; rhetorical structure theory; text summarisation. By Author: Samira Lagrini; Nabiha Azizi; Mohammed Redjimi; Monther Al Dwairi …

Are Better Summaries Also Easier to Understand? Analyzing Text Complexity in Automatic Summarization
E Lloret, T Vodolazova, P Moreda, R Muñoz… – World Scientific
… Text summarization and text simplification are research areas in natu- ral language processing that help to analyze information automatically. Text summarization aims to produce a shorter version of a document while preserving its key information and overall meaning …

An Extractive Based Multi-Document Summarization Using Weighted TF-IDF And Centroid Based K-Means Clustering (TF-IDF: CBC) …
J ROBINSON, V SARAVANAN – Journal of Critical Reviews, 2019 – jcreview.com
… complexity and memory usage. This paper proposes an Automatic text summarization method using the weighted TF-IDF model and K-means clustering for reducing the dimensionality of the extracted features. The various similarity …

Automatic Summarization of Legal Text
N Luijtgaarden – 2019 – dspace.library.uu.nl
… Current research on legal text summarization has only focused on extractive methods, which can result in awkward summaries as sentences in legal documents can be very long and detailed … 11 2.5 Legal text summarization …

Intelligent Summarization: Leveraging Cohesion in Text
AT Saseendran – 2019 – scss.tcd.ie
… Text summarization is a task that requires the application of human intelligence in which the human shows an understanding of natural language and can process lan- guage, where human beings show creativity by presenting complex objects and events …

Extractive Text-Based Summarization of Arabic videos: Issues, Approaches and Evaluations
MA Menacer, CE González-Gallardo, K Abidi… – … Conference on Arabic …, 2019 – Springer
… Keywords. Text summarization Video summarization Automatic speech recognition Segmentation. Download conference paper PDF. 1 Introduction … Class. F1-score. Boundary. 0.684. No boundary. 0.980. 6 Automatic Text Summarization …

Dependency graph for short text extraction and summarization
N Franciscus, X Ren, B Stantic – Journal of Information and …, 2019 – Taylor & Francis
… Many data mining applications have been devel- oped to help understand and to summarize these collections of texts, for example, topic modelling (Blei, Ng, & Jordan, 2003) and text summarization (Mihalcea & Tarau, 2004) …

FrameRank: A Text Processing Approach to Video Summarization
Z Lei, C Zhang, Q Zhang, G Qiu – 2019 IEEE International …, 2019 – ieeexplore.ieee.org
… In general, connection between frames can be con- sidered as a graph, where vertexes refers to the video frames and edges are the pairwise similarities. The initial idea was to transfer a video to text and per- form text summarization …

Automatic Summarization and Keyword Extraction from Web Page or Text File
X You – 2019 IEEE 2nd International Conference on Computer …, 2019 – ieeexplore.ieee.org
… [7] R. Mihalcea. 2004. Graph-based ranking algorithms for sentence extraction, applied to text summarization. In Proceedings of the 42nd Annual Meeting of the Association for Computational Lingusitics (ACL 2004) (companion volume),Barcelona, Spain. [8] DUC. 2002 …

Heterogeneous-Length Text Topic Modeling for Reader-Aware Multi-Document Summarization
J Qiang, P Chen, W Ding, T Wang, F Xie… – ACM Transactions on …, 2019 – dl.acm.org
Page 1. 42 Heterogeneous-Length Text Topic Modeling for Reader-Aware Multi-Document Summarization JIPENG QIANG, Yangzhou University PING CHEN, WEI DING, and TONG WANG, University of Massachusetts Boston …

Characterizing human summarization strategies for text reuse and transformation in literature review writing
K Jaidka, CSG Khoo, JC Na – Scientometrics, 2019 – Springer
Citations are useful signals of information salience, but little research has identified the patterns of information selection, transformation, and organization that they espouse. This paper…

Reading against the text? Metarepresentation and subjectivity patterns in the summarization of Henry James’s tales
JA Álvarez-Amorós – academia.edu
Page 1. 1 Reading against the text? Metarepresentation and subjectivity patterns in the summarization of Henry James’s tales José A. Álvarez-Amorós Published version: Journal of Literary Semantics 48.1 (2019): 59-83 jalvarez …

Reading against the text? Metarepresentation and patterns of subjectivity in the summarization of Henry James’s tales
JA Álvarez-Amorós – Journal of Literary Semantics, 2019 – degruyter.com
AbstractInformed by cognitive narratology and specifically based on our metarepresentational ability, this paper explores how the subjectivity in Henry James’s tales is transferred to the summaries provided by critics for the orientation of readers. Since it enables real, and realistic …