Abstractive Summarization 2016


abstractive summarization / abstractive summarisation

abstraction-based summarization / abstraction-based summarisation

Notes:

There are two general approaches to automatic summarization, extraction and abstraction. Abstractive methods build an internal semantic representation and then use natural language generation techniques to create a summary that is closer to what a human might generate. Such a summary might contain words not explicitly present in the original.

  • Automatic summarizer

Wikipedia:

References:

See also:

Machine Reading


The role of CNL and AMR in scalable abstractive summarization for multilingual media monitoring
B Davis – … Natural Language: 5th International Workshop, CNL …, 2016 – Springer
The Role of CNL and AMR in Scalable Abstractive Summarization for Multilingual Media Monitoring Normunds Gruzitis (&) and Guntis Barzdins IMCS and LETA, University of Latvia, Riga, Latvia normunds. gruzitis@ lumii. lv, guntis. barzdins@ leta. lv In the era of Big Data and Deep

A Review of Recent Developments in Abstractive Summarization Techniques
JR Silva – DSIE| 16 – researchgate.net
Abstract. Abstractive summarization techniques have evolved during the previous years since extraction-based methods fail to achieve a series of requirements necessary for a summary to be efficient. Abstraction aims to mimic the process of summarization in order to

Multilingual Natural Language Generation within Abstractive Summarization.
S Mille, M Ballesteros, A Burga, G Casamayor… – MMDA@ ECAI, 2016 – ceur-ws.org
Abstract. With the tremendous amount of textual data available in the Internet, techniques for abstractive text summarization become increasingly appreciated. In this paper, we present work in progress that tackles the problem of multilingual text summarization using semantic

Abstractive Summarization for Amazon Reviews
L Yang – cs224d.stanford.edu
Abstract This paper focuses on feed-forward neural network with attention-based encoder to solve the challenge of abstractive summarization. We also briefly explored the potential of attentive recurrent neural network and recurrent neural network encoder-decoder. Those

Improving Neural Abstractive Text Summarization with Prior Knowledge
G Rossiello, P Basile, G Semeraro, M Di Ciano… – 2016 – lia.disi.unibo.it
… Abstractive Summarization The generated summary is a new cohesive text not necessarily present in the original source. Gaetano Rossiello, et al. Neural Abstractive Text Summarization Page 5. … Page 6. Abstractive Summarization: a Challenging Task …

AN AUTOMATIC DOCUMENT SUMMARIZATION SYSTEM USING A FUSION METHOD
R Mol, KP Sabeeha – 2016 – irjet.net
… summary. So, extractive summarization and abstractive summarization approaches are used. Extractive … summary. Abstractive summarization method which generates a summary that is closer to what a human might create. Basically …

Statistical and analytical study of guided abstractive text summarization
JS Kallimani, KG Srinivasa, BE Reddy – CURRENT SCIENCE, 2016 – currentscience.ac.in
… The process of creating condensed version of given text document by collecting only the important infor- mation in it is called abstractive summarization. … Research in abstractive summarization methodologies for Indian regional languages has started recently. …

Neural Abstractive Text Summarization.
G Rossiello – DC@ AI* IA, 2016 – ceur-ws.org
… Abstractive summarization requires deep understanding and reasoning over the text, determining the explicit or implicit meaning of each element, such as words, phrases, sentences and paragraphs, and making inferences about their properties [ ] in order to generate new …

Single or Multi-document Summarization Techniques
M Bhide – ijcstjournal.org
… information. Different approaches of summarization include extractive and abstractive summarization, semantic and syntactic techniques of summarization which may utilize supervised or unsupervised learning algorithms. Comparison …

NLP Based Text Summarization Using Semantic Analysis
HS Moiyadi, H Desai, D Pawar, G Agrawal, NM Patil – ijaems.com
… In 2016, Dr.A.Jaya et al, studied the various techniques available for abstractive summarization and put forward the fact that very little work is available in abstractive summary field of Indian languages. … A Study on Abstractive Summarization Techniques in Indian Languages …

Framework for Smart Medicine Advisor Dictionary using Natural Language Processing
S Pooja, MP Vijay – ijarcet.org
… clustering, summarization etc. The stream of concept is useful for relationship extraction. Document summarization can be done using two methods, they are Extractive and abstractive summarization. Extractive is the technique …

CaseSummarizer: A System for Automated Summarization of Legal Texts.
S Polsley, P Jhunjhunwala, R Huang – COLING (Demos), 2016 – aclweb.org
… Summaries are usually generated by extracting ‘important’ portions of the text. Extraction-based methods are often used because abstraction-based summarization is an open problem in NLP. Abstraction-based summarization …

Multilingual Multi-document Summarization with Enhanced hLDA
T Huang, L Li, Y Zhang – cips-cl.org
… Extractive sum- marization aims to select important sentences from the original document and reorganize these sentences according to their order, while abstractive summarization aims to understand the original text and re-tell it like human. …

An Extractive Approach for Uyghur Text Summarization
TTHYA Hamdulla – 2016 – researchgate.net
… According to the way of generation, automatic summarization can be divided into two categories, namely extractive summarization and abstractive summarization [1]. There is high summary quality of abstractive summarization and has the advantages of concise, comprehensive …

An Ontology-based Automatic Text Summarization: Survey
B Azman, IA Al-Baltah – researchgate.net
… Abstractive summarization is an automatic summarization that builds an internal semantic representation and then use natural language generation techniques to create a summary that is closer to what a human might generate. …

A Publicly Available Indonesian Corpora for Automatic Abstractive and Extractive Chat Summarization.
F Koto – LREC, 2016 – lrec-conf.org
… Whereas, abstractive summarization is a more advanced summariza- tion which involves natural language technique in building … Genest and Lapalme (2012) de- veloped and implemented a fully abstractive summarization methodology in the context of guided summarization. …

Modeling Extractive Sentence Intersection via Subtree Entailment.
O Levy, I Dagan, G Stanovsky, J Eckle-Kohler… – COLING, 2016 – aclweb.org
… Marsi and Krahmer, 2005; McKeown et al., 2010; Thadani and McKeown, 2011), is to construct a sentence containing all the information shared by the two input sentences (Figure 1). While sentence intersection was originally proposed for abstractive summarization, we argue …

Summarising the points made in online political debates
C Egan, A Siddharthan, A Wyner – ACL 2016, 2016 – aclweb.org
… In this paper, we propose a fully automatic and domain neutral unsupervised approach to abstractive summarisation which makes the key content of such discussions accessible. … 3.3 Summary Generation Our goal is the abstractive summarisation of argumentative texts. …

The Role of Discourse Units in Near-Extractive Summarization.
JJ Li, K Thadani, A Stent – SIGDIAL Conference, 2016 – anthology.aclweb.org
… In contrast, when the task at hand is more abstractive, the units are more fine- grained, eg, n-grams and phrases in abstractive summarization (Kikuchi et al., 2014; Liu et al., 2015; Bing et al., 2015), n-grams and human- annotated concept units in summarization evalu- ation (Lin …

Explorations in Identifying and Summarizing Subjective Content in Text
P Kumar, V Venugopal – cs224d.stanford.edu
… opinions. The first is the identification of subjective phrases in text, and the second is the abstractive summarization of opinionated text. Deep … Our second task is the abstractive summarization of opinionated texts. Unlike extractive …

Journal of Soft Computing and Decision Support Systems
YA AL-Khassawneh, N Salim… – Journal of Soft Computing …, 2016 – researchgate.net
… Keywords: Text summarization, Extractive summarization, Abstractive summarization, Sentence similarity … Thus, it can be construed that the objective of abstraction based summarization is to produce (as humans do) a summary comprising grammatically flawless fresh …

Unsupervised Text Summarization Using Sentence Embeddings
A Padmakumar, A Saran – pdfs.semanticscholar.org
… summarization task are relatively small in size. Another broad classification of summarization tech- niques is into extractive and abstractive summarization. … Opinosis: a graph-based approach to abstractive summarization of highly redundant opinions. …

Abstractive tweet stream summarization using natural language processing
S Annamalai, R Sudharsan, RT Raj – International journal of advances in …, 2016 – troindia.in
… The results are evaluated based on the contextual significance of the summary. Keywords: tweet stream, summary, abstractive summarization, incremental clustering … This causes a major lack of information which can be overcome by abstractive summarization. VI. …

Beyond Utterance Extraction: Summary Recombination for Speech Summarization.
J Trione, B Favre, F Béchet – Interspeech, 2016 – pdfs.semanticscholar.org
… A good overview of the state of the art in automatic summariza- tion can be found in [2]. Additional references for abstractive summarization can be found in [3]. Even recent work charac- terized as abstractive, for generating sentences from recombi- nations of the source …

Unsupervised Text Recap Extraction for TV Series.
H Yu, S Zhang, LP Morency – EMNLP, 2016 – pdfs.semanticscholar.org
… Generally, there are two approaches: extractive and abstractive summarization. Extractive summarization forms a summary by choosing the most representative sentences from the original corpus. … Abstractive summarization automatically create new sentences. …

Tweet Streams Online Summarization and Timeline Generation
MGG Dayalani – INTERNATIONAL JOURNAL, 2016 – pdfs.semanticscholar.org
… Extractive summarization is a process in which the sentences are selected from the number of documents itself, while abstractive summarization produces the phrases which may not be present in the actual existing document. …

A Novel Approach for Tweet Summarization through Timeline Generation
GS Harika, M Sreenivasulu – ijcsest.com
… Extractive summarization is a process in which the sentences are selected from the number of documents itself, while abstractive summarization produces the phrases which may not be present in the actual existing document.Salient scores are assigned to the sentences of the …

Summarizing Text Using Lexical Chains
P Jain, S Jain – academia.edu
… Fig 1.1: Text Summarization . II. CLASSIFICATION OF TEXT SUMMARIZATION Text summarization strategies are often classified into extractive and abstractive summarization [2]. An extractive summarization technique consists of choosing necessary sentences, paragraphs etc. …

Neural Text Summarization
U Khandelwal – cs224d.stanford.edu
… We work with abstractive summarization and treat the input vocabulary, VX , as separate from the output *Joint work with Peng Qi and Dan Jurafsky 1 Page 2. Figure 1: Sequence to Sequence model (image from Sutskever et. al (2014)). …

A Model for Employing Semantic Role Labeling To Extract Predicate Argument Structure
HAM Elsied, N Salim, A Khan – ijcstjournal.org
… 4]. In the area of text summarization, [5]introduced a work that combined semantic role labeling with general statistic method (GSM) to determine important sentences for single document extractive summary, also [6] introduce a work of abstractive summarization uses SRL. …

AN OVERVIEW OF EXTRACTIVE BASED AUTOMATIC TEXT SUMMARIZATION SYSTEMS
DMN Mubarak – pdfs.semanticscholar.org
… The Abstractive summarization system understands the main concept of texts and predicts the overall idea about the topic. … KEYWORDS: Text summarization, Abstractive summarization, Extractive summarization, Statistical methods, Latent semantic analysis. 1. INTRODUCTION …

A Survey on A hybrid method for query based automatic summarization system for text
S Leuva, APP Jardosh, GTU SOCET – iit-rd.com
… It extracts the most important part based on statistical and linguistic features such as cue words, location, and word frequency Abstractive approaches: Abstractive-summarization understands the whole document and then generates the summary. …

Using Facebook Public Posts to Enhance Trending News Summarization
C Li, Z Wei, Y Liu, Y Jin, F Huang – research.fb.com
… 5 Abstractive Summarization Method and Results 5.1 Dependency Tree Based Compression … Therefore next we investi- gate abstractive summarization by applying sentence compression when extracting sentences from news to improve summarization performance. …

Content Selection through Paraphrase Detection: Capturing different Semantic Realisations of the Same Idea
E Lloret, C Gardent – WebNLG 2016, 2016 – anthology.aclweb.org
… 2 Related Work Abstractive summarisation is one of the most chal- lenging issues to address automatically, since it both requires deep language understanding and generation with a strong semantic … 2011. Framework for abstractive summarization using text-to-text generation. …

GENERATING SUMMARIES USING SENTENCE COMPRESSION AND STATISTICAL MEASURES
S Roy – aircconline.com
… On the other hand, abstraction based summarization does not rely on simple extraction to generate summary; instead it does so by forming new sentences intuitively from the given document(s). Most of the pre … [5] proposed a graph based abstractive summarization system called …

Distraction-Based Neural Networks for Modeling Document.
Q Chen, XD Zhu, ZH Ling, S Wei, H Jiang – IJCAI, 2016 – ustc.edu.cn
… In general, our models here aim to perform abstractive summarization. 2 Related work … Most state- of-the-art summarization models have focused on extractive summarization, although some efforts have also been exerted on abstractive summarization. …

SURVEY OF EXTRACTIVE BASED AUTOMATIC TEXT SUMMARIZATION TECHNIQUES
SS Naik, MN Gaonkar – ijetcse.com
… Therefore, abstractive summarization is little more tedious to carry out than extractive summarization. … [7] Atif Khan and Naomie Salim, “A review on abstractive summarization methods,” Journal of Theoretical and Applied Information Technology,10th January 2014. vol. …

Cluster Based And Graph Based Methods Of Summarization: Survey And Approach
S Hinge, S Sonawane – International Journal of Computer Engineering and … – ijcea.com
… Contrast to extractive summarization, abstractive summarization works on concept of a document/text and generate new sentences from the concept. Sentence fusion, semantic analysis is mainly used to generate new sentences from original sentences. …

Using Relevant Public Posts to Enhance News Article Summarization.
C Li, Z Wei, Y Liu, Y Jin, F Huang – COLING, 2016 – aclweb.org
… 5 Abstractive Summarization Method and Results … The abstractive summarization experiments are based on the setup of System ‘d’, that is, we extract sentences from the news articles, but the bigrams and their weight information come from both the news and the posts. …

Generating bags of words from the sums of their word embeddings
L White, R Togneri, W Liu… – … Conference on Intelligent …, 2016 – white.ucc.asn.au
… A similar use is the replacement of vector based extractive summarisation (Kågebäck et al. 2014; Yogatama et al. 2015), with keyword based abstractive summarisation, which is the generation of a keyword summary from a document. …

MUSEEC: A Multilingual Text Summarization Tool
M Litvak, N Vanetik, M Last, E Churkin – ACL 2016, 2016 – aclweb.org
… Unlike the abstractive summarization methods, which require natural language processing oper- ations, language-independent summarizers work in an extractive manner, usually via ranking frag- ments of a summarized text by a relevance score and selecting the top-ranked …

Summarization and Sentiment Analysis for Understanding Socially-Generated Content
L Wang – 2016 – ccs.neu.edu
… 10 2.1.2 Extractive vs. Abstractive Summarization . . . . . … 2.1.2 Extractive vs. Abstractive Summarization For the past decades, the most prominent multi-document summarization approaches have been extractive summarization methods, where sentences from the original …

A Hybrid Approach to Generation of Missing Abstracts in Biomedical Literature.
SK Chachra, AB Abacha, SE Shooshan, L Rodriguez… – COLING, 2016 – aclweb.org
… 1093 Page 2. extractive methods are as effective as abstractive summarization or text generation. Kim et al. proposed a sub-topic or theme detection method for multi-document clustering and topical summarization of citation data (Kim et al., 2015). …

SOME IMPROVEMENTS OF THE OPEN TEXT SUMMARIZER ALGORITHM USING HEURISTICS
F ANDONOV, V SLAVOVA – ceeol.com
… This led to the idea to concentrate the tool around the word-forms score. We think that abstraction-based summarization is hard enough to be more of a scientific gymnastic than a practical solution, so we are focusing on extraction-based summarization. Basic scheme Figure …

Data-driven Paraphrasing and Stylistic Harmonization.
G Hintz – SRW@ HLT-NAACL, 2016 – anthology.aclweb.org
… This requires detecting semantic equivalences be- tween sentences. Abstractive summarization re- quires a system to further rephrase the summary, to match space constraints, achieve fluency, or unify stylistic differences in multiple source documents. …

TEXT SUMMARIZATION
R Nallapati, B Xiang, B Zhou – arXiv preprint arXiv …, 2016 – pdfs.semanticscholar.org
… There has also been some work on abstractive summarization using traditional machine translation based models (Banko et al. (2000)). In the framework of deep learning, the closest to our model is the recent work of Rush et al. …

Specifying and annotating reduced argument span via qa-srl
GSMAI Dagan – The 54th Annual Meeting of the Association for …, 2016 – aclweb.org
… However, in certain applications, such as ques- tion answering or abstractive summarization, a re- duced argument is preferred (ie,“Obama”). No- tably, different implementations of Open-IE pro- vide an applicable generic way to reduce argument span. …

Pruning Document Data using Top-K Rule for Effectively Summarized Text
MPJ Patel, PG Kulurkar – ijiset.com
… documents of text. Text Summarization methods can be classified into abstractive and extractive summarization. Abstractive summarization aims at paraphrasing the source document, similar to manual summarization. An extractive …

A Hierarchical Model for Text Autosummarization
Z Zhou – cs224d.stanford.edu
… ation. Banko et al. [15] showed work using statistical machine translation directly for abstractive summarization. Cohn and Lapata [16] give a tree transduction compression method with a max- margin learning algorithm. Deep …

An Advanced approach for Summarization and Timeline Generation of Evolutionary Tweet Streams
P Sindhuja, J Suneetha – ijarcet.org
… Similarly, in image collection summarization, the system extracts images from the collection without modifying the images themselves. On the other hand, abstraction based summarization task, involves paraphrasing sections of the source document. …

Won’t somebody please think of the children? Improving Topic Model Clustering of Newspaper Comments for Summarisation
C Llewellyn, C Grover, J Oberlander – ACL 2016, 2016 – anthology.aclweb.org
… would take. 2.1. 1 Comment Summarisation Abstractive summarisation is a very complex task, and because comment summarisation is a rela- tively new task, current work mostly focuses on extractive approaches. The general …

Development Of Automatic Text Summarizer For PDF Files
OE OYINLOYE, O Fatai, OA Aliu – Development, 2016 – jmest.org
… [8] KavitaGanesan, ChengXiangZhai and Jiawei Han (2010); Opinosis: A Graph-Based Approach to Abstractive Summarization of Highly Redundant Opinions; Department of Computer Science, University of Illionis at Urbana- Champaign, Pg 1 – 3. …

Controlled Natural Language
B Davis, GJ Pace, A Wyner – Springer
… 123 Aarne Ranta Page 10. The Role of CNL and AMR in Scalable Abstractive Summarization for Multilingual Media Monitoring….. 127 Normunds Gruzitis and Guntis Barzdins Author Index….. 131 X Contents Page 11.

Extractive and Abstractive Event Summarization over Streaming Web Text.
C Kedzie, K McKeown – IJCAI, 2016 – ijcai.org
… sentences without modification from the input documents. In abstractive summarization, the summary is written in whole or in part by an abstractive text generation algorithm. Common approaches to abstractive text generation …

Survey On Data Stream Clustering And Summarization
DA Nevase, A Priyadarshi – ardigitech.in
… 2.2 Document Summarization Document summarization is classified as extractive & abstractive summarization. Abstraction involves paraphrasing sections of the source document. Extractive performs the automatic system extracts …

WikiWrite: Generating Wikipedia Articles Automatically.
S Banerjee, P Mitra – IJCAI, 2016 – ijcai.org
… In contrast, we pro- pose an integrated framework for multi-document abstractive summarization. 3 Proposed Approach Our goal is to construct articles for notable6 Wikipedia enti- ties that do not have corresponding articles. Figure 1 shows our proposed framework of WikiWrite. …

Abstractive Cross-Language Summarization via Translation Model Enhanced Predicate Argument Structure Fusing
TMEP Argument – ieeexplore.ieee.org
Page 1. 2329-9290 (c) 2016 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …

Abstractive Compression of Captions with Attentive Recurrent Neural Networks
S Wubben, E Krahmer, A Bosch, S Verberne – 2016 – repository.ubn.ru.nl
… for higher ROUGE scores. Following this work, we employ an attentive Re- current Network as described in (Bahdanau et al., 2014) to the task of abstractive summarization of scene descriptions. 3 Data set To construct the data …

Web Data Linking through Knowledge Based for Accessing Information Based on Entity Linking
M Sravani, SR Swamy, M Sidhar – ijcsest.com
… To exhibit that our procedure can notice the emergence of a new matter as a minimum as speedy as making use of the best term that was not obvious at the moment. A. Document Summarization Document summarization is classified as extractive & abstractive summarization. …

The Kyutech corpus and topic segmentation using a combined method
T Yamamura, K Shimada… – The 12th Workshop on …, 2016 – anthology.aclweb.org
… However, the main purpose is to summarize a multi-party conversation. Abstractive summarization using the segmented topics is also the important future work. … 2014. Abstractive summarization of spoken and written conversations based on phrasal queries. …

Summarization of Changes in Dynamic Text Collections
M Kar – 2016 – repositorio-aberto.up.pt
Page 1. : ´ ( . . Doctoral Program in Informatics of the Universities of Minho, Aveiro, and Porto (MAPi) Page 2. Manika Kar: Summarization of Changes in Dynamic Text Collections, Ph.D. The- sis, c 2016, June. – : manika.kar@gmail.com Page 3. ABSTRACT …

Concept Based Sentence Modeling for Extractive Speech Summarization
G keerthana Gaddam – ijercse.com
… All Rights Reserved © 2016 IJERCSE 5 investigating abstractive summarization which reflects the main theme of document. But it requires some difficult implementations of NLP and NLG techniques along with semantics. REFERENCES …

A Proposed Textual Graph Based Model for Arabic Multi-document Summarization
MA Alwan, HM Onsi – INTERNATIONAL JOURNAL OF …, 2016 – pdfs.semanticscholar.org
… We are interested in multi- document abstractive summarization approaches that almost can be applied to Arabic language. … 449–460. [6] F. Liu, J. Flanigan, S. Thomson, N. Sadeh, and NA Smith, “Toward abstractive summarization using semantic representations,” 2015. …

Topic Detection and Summarization of Events on Social Media Data
RD Gavali, AR Kulkarni – pdfs.semanticscholar.org
… CHI-11, 2011, pp. 227–236. [10] Gulab R. Shaikh, Digambar M. Padulkar “Template Based Abstractive Summarization of Twitter Topic with Speech Act” by Asst. Prof., Department of CSE, VPCOE Baramati, Pune, India, India in June 2014. IJCATM : www.ijcaonline.org

A Report to the Board of Scientific Counselors April 2016
D Demner-Fushman, J Mork – 2016 – lhncbc.nlm.nih.gov
… In this report, we will refer to MTI functions as automated in- dexing, using the sense of the term that pertains to deriving documents’ characteristics and main points automatically, similar to automated abstractive summarization. …

An Academic Search Engine and Problems in Citation Networks
AA Narwekar – 2016 – abhisheknkar.net
… This problem has been approached in two ways: by extractive and by abstractive summarization. In an academic … Abstractive Summarization While plenty of work has been done on extractive summarization, abstractive summarization remains a relatively understudied area. …

The MULTISENSOR Project-Development of Multimedia Content Integration Technologies for Journalism, Media Monitoring and International Exporting …
D Liparas, S Vrochidis, I Kompatsiaris, G Casamayor… – MMDA@ ECAI, 2016 – ceur-ws.org
… 2. Abstractive summarisation: Documents are analysed and the in- formation extracted from them is used to generate a summary that is not composed of fragments of the original documents, but is generated directly from data. …

Enhancing The RATP-DECODA Corpus With Linguistic Annotations For Performing A Large Range Of NLP Tasks.
C Lailler, A Landeau, F Béchet, Y Estève, P Deléglise – LREC, 2016 – lrec-conf.org
… time the main topic, the interaction and the final result. These summaries are a great opportunity to evaluate abstractive summarization methods of human- human dialogues. A pilot task was proposed at Multiling 2015 (Favre …

Multiple Aspect Ranking Using Sentiment Classification for Data Mining
NAR Vasanthi – pdfs.semanticscholar.org
… Existing review summarization methods can be classified into abstractive and extractive summarization. An abstractive summarization attempts to develop an understanding of the main topics in the source reviews and then express those topics in clear natural language. …

Building concept graphs from monolingual dictionary entries
GA Recski – 2016 – real.mtak.hu
… Task, pages 28–34. Association for Computa- tional Linguistics. Liu, F., Flanigan, J., Thomson, S., Sadeh, N., and Smith, NA (2015). Toward abstractive summarization using semantic representations. In Proceedings of the 2015 …

1st International Workshop on Multimodal Media Data Analytics (MMDA 2016)
S Vrochidis, M Melero, L Wanner, J Grivolla, Y Estève… – ecai2016.org
… for automatic speech recognition • S. Mille, M. Ballesteros, A. Burga, G. Casamayor and L. Wanner, Multilingual Natural Language Generation within Abstractive Summarization • J. Codina-Filbà and L. Wanner, Combining Dictionary- and Corpus-Based Concept Extraction …

An Extractive Multi-Document Summarization Technique Based on Fuzzy Logic approach
ML VARUS – ieeexplore.ieee.org
… And each one has given 2 documents on the same topic and two summaries from those documents generated with two different summarization techniques which are extractive abstractive summarization technique and Timestamp comparator. …

Hybrid Algorithm to Evaluate E-Business Website Comments
OM Rababah, AK Hwaitat, DA Al Qudah, R Halaseh – 2016 – file.scirp.org
… [18] Carenini, G. and Cheung, J. (2008) Extractive vs. NLG-Based Abstractive Summarization of Evaluative Text: The Ef- fect of Corpus Controversiality. Proceedings of the International Natural Language Generation Conference, 33-41. …

Generating Headlines with Recurrent Neural Networks
A EVERT, J GENANDER, N LALLO, R LANTZ… – publications.lib.chalmers.se
… A statistical model can be used for tasks where the next word in a sequence is to be predicted, for example auto-completion in smartphone keyboards, whereas a conditioned model could be used for abstractive summarization tasks. …

WHISK: Web Hosted Information into
J Wu – 2016 – pdfs.semanticscholar.org
… The simplified models removes unnecessary restrictions in- herited from Opinosis graph’s abstractive summarization origins. Performance mea- … into two approaches: abstractive and extractive. The abstractive summarization approach aims to create novel sentences that cap- …

Word Sense Embedded in Geometric Spaces
M KÅGEBÄCK – pdfs.semanticscholar.org
… contrast, extractive summarisation picks the most important sentences from the docu- ments and put them together to form the summary, See Figure 3.3.1. Though abstractive summarisation more resemble how humans summarise text, extractive summarisation has so far been …

CIST System for CL-SciSumm 2016 Shared Task.
L Li, L Mao, Y Zhang, J Chi, T Huang… – BIRNDL …, 2016 – pdfs.semanticscholar.org
Page 1. CIST System for CL-SciSumm 2016 Shared Task Lei Li, Liyuan Mao, Yazhao Zhang, Junqi Chi, Taiwen Huang, Xiaoyue Cong, Heng Peng Center for Intelligence Science and Technology (CIST), School of Computer …

A Joint Model of Rhetorical Discourse Structure and Summarization
N Goyal, J Eisenstein – EMNLP 2016, 2016 – aclweb.org
… compression (Berg-Kirkpatrick et al., 2011). The combination of the proposed ap- proach with abstractive summarization via sentence compression might yield better results on summa- rization metrics. Discourse structure has also been …

VSoLSCSum: Building a Vietnamese Sentence-Comment Dataset for Social Context Summarization
MT Nguyen, VD Lai, PK Do, DV Tran… – The 12th Workshop on …, 2016 – aclweb.org
… [Ganesan et al. 2010] Kavita Ganesan, ChengXiang Zhai, and Jiawei Han. 2010. Opinosis: a graph-based approach to abstractive summarization of highly redundant opinions. In COLLING: 340-348. [Gao et al. 2012] Wei Gao, Peng Li, and Kareem Darwish. 2012. …

Product Review Summarization by Exploiting Phrase Properties.
N Yu, M Huang, Y Shi, X Zhu – COLING, 2016 – aclweb.org
… Springer. Siddhartha Banerjee, Prasenjit Mitra, and Kazunari Sugiyama. 2015. Multi-document abstractive summarization using ilp based multi-sentence compression. In 24th International Joint Conference on Artificial Intelligence (IJCAI). Buenos Aires, Argentina: AAAI press. …

Scalable algorithms for scholarly figure mining and semantics.
SR Choudhury, S Wang, CL Giles – SBD@ SIGMOD, 2016 – pdfs.semanticscholar.org
… [8] CF Greenbacker, P. Wu, S. Carberry, KF McCoy, and S. Elzer. Abstractive summarization of line graphs from popular media. In Proceedings of the Workshop on Automatic Summarization for Different Genres, Media, and Languages, pages 41–48. …

Selecting Domain-Specific Concepts for Question Generation With Lightly-Supervised Methods.
Y Jin, P Le – INLG, 2016 – anthology.aclweb.org
… Ai Communi- cations, 22 (3): 153–186. Pierre-Etienne Genest and Guy Lapalme. 2010. Text generation for abstractive summarization. In Proceed- ings of the Third Text Analysis Conference, Gaithers- burg, Maryland, USA. National Institute of Standards and Technology. …

RECOGNIZING SUPERLATIVE COMMENTS OF AN ARTIFACTS USING SOCIAL MEDIA AND RANKING
DGS Ikkurthi Gopinath – ijtra.com
Page 1. International Journal of Technical Research and Applications e-ISSN: 2320-8163, www.ijtra.com Volume 4, Issue 2 (March-April, 2016), PP. 91-107 91 | Page RECOGNIZING SUPERLATIVE COMMENTS OF AN ARTIFACTS USING SOCIAL MEDIA AND RANKING …

An argumentation-based approach to summarizing discussions
C Egan – 2016 – charlieegan3.com
… or multiple documents. This project is more closely related to the summarization of multiple documents and applies both elements of extractive and abstractive summarization. Multi-document Summarization Summarizing text …

Algorithms and Applications for Web-Scale Knowledge Graphs
M Ponza – 2016 – di.unipi.it
Page 1. Universit`a degli Studi di Pisa Dipartimento di Informatica Dottorato di Ricerca in Informatica Algorithms and Applications for Web-Scale Knowledge Graphs Ph.D. Thesis Proposal October 2016 Marco Ponza marco.ponza@di.unipi.it Supervisor Prof. …

Arabic XML documents: summarizing, managing, and securing
H Naser Elzentani – 2016 – nardus.mpn.gov.rs
Page 1. SINGIDUNUM UNIVERSITY Department of Postgraduate Studies DOCTORAL DISSERTATION ARABIC XML DOCUMENTS: SUMMARIZING, MANAGING, AND SECURING Mentor: Candidate: _____ _____ Prof. …

Countering Security Threats Using Natural Language Processing
P Isabelle, C Cherry, R Kuhn, S Mohammad – 2016 – cradpdf.drdc-rddc.gc.ca
Page 1. Countering Security Threats Using Natural Language Processing Pierre Isabelle C. Cherry R. Kuhn S. Mohammad National Research Council Prepared By: National Research Council 1200 Montreal Rd., Building M-50 Ottawa, ON K1A 0M5 …

Adapting Spoken Dialog Systems Towards Domains and Users
M Sun – 2016 – lti.cs.cmu.edu
Page 1. Adapting Spoken Dialog Systems Towards Domains and Users Ming Sun CMU-LTI-16-006 Language Technologies Institute School of Computer Science Carnegie Mellon University 5000 Forbes Ave., Pittsburgh, PA 15213 www.lti.cs.cmu.edu …

Content and Context in Conversations: The Role of Social and Situational Signals in Conversation Structure
F Bonin – 2016 – tara.tcd.ie
Page 1. Content and Context in Conversations: The Role of Social and Situational Signals in Conversation Structure Francesca Bonin Thesis submitted for the Degree of Doctor of Philosophy School of Computer Science & Statistics Trinity College University of Dublin Page 2. …

Text Analytics with Python
D Sarkar – Springer
Page 1. Text Analytics with Python A Practical Real-World Approach to Gaining Actionable Insights from Your Data — Dipanjan Sarkar Page 2. Text Analytics with Python A Practical Real-World Approach to Gaining Actionable Insights from your Data Dipanjan Sarkar Page 3. …