There are several options for extracting complete sentences from a text, including:
- Regular expressions: A pattern-matching method that can be used to identify and extract complete sentences from a text.
- Natural language processing (NLP) libraries: There are various NLP libraries available that include tools for sentence extraction, such as NLTK, SpaCy, and CoreNLP.
- Machine learning models: Sentence extraction can also be performed using machine learning algorithms, such as support vector machines or decision trees, which can be trained on labeled data to identify and extract complete sentences.
- Rule-based systems: A rule-based approach involves defining a set of rules or heuristics for identifying complete sentences, and then applying these rules to the text to extract the sentences.
- Hybrid approaches: It is also possible to combine multiple methods, such as using regular expressions in combination with NLP tools or machine learning models, to improve the accuracy and reliability of sentence extraction.
There are several tools and techniques available for sentence extraction based on grammar rather than punctuation. Here are a few examples:
- Part-of-speech (POS) tagging: This is a technique that involves labeling each word in a sentence with its part of speech (e.g., noun, verb, adjective). POS tagging can be used to identify the boundaries of sentences, as well as to identify the structure and meaning of a sentence.
- Dependency parsing: This is a technique that involves analyzing the grammatical structure of a sentence and identifying the relationships between the words in the sentence (e.g., subject-verb-object relationships). Dependency parsing can be used to identify the boundaries of sentences and to extract meaningful information from a text.
- Named entity recognition (NER): This is a technique that involves identifying and labeling named entities (e.g., people, organizations, locations) in a text. NER can be used to identify the boundaries of sentences and to extract important information from a text.
- Syntactic parsing: This is a technique that involves analyzing the grammatical structure of a sentence and identifying its constituent parts (e.g., noun phrases, verb phrases). Syntactic parsing can be used to identify the boundaries of sentences and to extract meaningful information from a text.
There are several neural network-based tools and techniques available for sentence extraction based on grammar rather than punctuation. Here are a few examples:
- Recurrent neural networks (RNNs): RNNs are a type of neural network that are well-suited for processing sequential data, such as text. RNNs can be used to perform POS tagging, dependency parsing, and named entity recognition, among other tasks.
- Graph neural networks (GNNs): GNNs are a type of neural network that are designed to operate on graph-structured data. GNNs can be used to perform syntactic parsing and dependency parsing, among other tasks.
- Transformer models: Transformer models are a type of neural network that have achieved state-of-the-art performance on many NLP tasks, including sentence classification and language translation. Transformer models can be used to perform sentence extraction and other NLP tasks.
There are many open-source libraries and frameworks available that implement these types of neural networks, including TensorFlow, PyTorch, and Hugging Face.
A graph neural network (GNN) is a type of neural network that is designed to operate on graph-structured data, such as networks or data that can be represented as nodes and edges. GNNs are particularly useful for modeling relationships and dependencies between data points, and have been used in a wide range of applications, including natural language processing (NLP), social network analysis, and recommendation systems.
GNNs can be used for sentence extraction by treating each sentence in a document as a node in a graph, and using the edges to represent the relationships between the sentences. For example, the edges could represent the dependencies between the sentences, such as which sentences provide background information or context for other sentences.
Once the graph has been constructed, the GNN can be used to process the graph and extract the most relevant or important sentences. This can be done by training the GNN to predict which sentences are most relevant or important based on a set of labeled examples, or by using the GNN to score the sentences based on their relationships to other sentences in the graph.
The references below discuss various methods for automatic summarization of text, including sentence extraction and ranking, information distillation, and fuzzy-rough sets. These methods are applied to a variety of text types, including legal documents, gene information, and spontaneous presentations, and are used to extract key sentences or relevant information for the purpose of understanding large volumes of text quickly. The references also discuss the evaluation of these methods and the importance of considering sentence concatenation in summaries.
Sentence concatenation refers to the process of joining or combining multiple sentences into a single continuous string of text. This can be done for various purposes, such as to create a summary of a longer text, to improve the flow or coherence of a text, or to simplify the structure of a text for easier understanding. Sentence concatenation is often used in natural language processing and text summarization tasks, where it can help to reduce the length of a text while still preserving its meaning and important information.
100 Best GitHub: Sentence Boundary | Sentence Boundary Disambiguation & Dialog Systems | Sentence Extraction Module | Sentence Extractor | Sentence Generation Module | Sentence Grammaticality | Sentence Parsers & Dialog Systems | Sentence Patterns & Dialog Systems | Sentence Recognizer | Sentence Splitter 2011 | Sentence Splitting & Dialog Systems | Sentence Summarization
Graph-based ranking algorithms for sentence extraction, applied to text summarization R Mihalcea – Proceedings of the ACL 2004 on Interactive poster and …, 2004 – dl.acm.org Abstract This paper presents an innovative unsupervised method for automatic sentence extraction using graph-based ranking algorithms. We evaluate the method in the context of a text summarization task, and show that the results obtained compare favorably with … Cited by 202 Related articles All 12 versions
Comments-oriented blog summarization by sentence extraction M Hu, A Sun, EP Lim – Proceedings of the sixteenth ACM conference on …, 2007 – dl.acm.org Abstract Much existing research on blogs focused on posts only, ignoring their comments. Our user study conducted on summarizing blog posts, however, showed that reading comments does change one’s understanding about blog posts. In this research, we aim to … Cited by 86 Related articles All 14 versions
Improved Machine Translation Performance via Parallel Sentence Extraction from Comparable Corpora. DS Munteanu, A Fraser, D Marcu – HLT-NAACL, 2004 – mt-archive.info Abstract We present a novel method for discovering parallel sentences in comparable corpora. We train a maximum entropy classifier that, given a pair of sentences, can reliably determine whether or not they are translations of each other. Using this approach we … Cited by 67 Related articles
Sentence extraction-based presentation summarization techniques and evaluation metrics. M Hirohata, Y Shinnaka, K Iwano, S Furui – ICASSP (1), 2005 – g.csie.org ABSTRACT This paper presents automatic speech summarization techniques and its evaluation metrics, focusing on sentence extraction-based summarization methods for making abstracts from spontaneous presentations. Since humans tend to summarize … Cited by 44 Related articles All 5 versions
Summarization with a joint model for sentence extraction and compression AFT Martins, NA Smith – Proceedings of the Workshop on Integer Linear …, 2009 – dl.acm.org Abstract Text summarization is one of the oldest problems in natural language processing. Popular approaches rely on extracting relevant sentences from the original documents. As a side effect, sentences that are too long but partly relevant are doomed to either not appear … Cited by 42 Related articles All 11 versions
Sentence Extraction Based Single Document Summarization J Jagadeesh, P Pingali, V Varma – International Institute of …, 2005 – web2py.iiit.ac.in Abstract The need for text summarization is crucial as we enter the era of information overload. In this paper we present an automatic summarization system, which generates a summary for a given input document. Our system is based on identification and extraction … Cited by 23 Related articles
Assessing the impact of lexical chain scoring methods and sentence extraction schemes on summarization W Doran, N Stokes, J Carthy, J Dunnion – Computational Linguistics and …, 2004 – Springer Abstract We present a comparative study of lexical chain-based summarisation techniques. The aim of this paper is to highlight the effect of lexical chain scoring metrics and sentence extraction techniques on summary generation. We present our own lexical chain-based … Cited by 27 Related articles All 15 versions
Using outcome polarity in sentence extraction for medical question-answering Y Niu, X Zhu, G Hirst – AMIA Annual Symposium Proceedings, 2006 – ncbi.nlm.nih.gov Abstract Multiple pieces of text describing various pieces of evidence in clinical trials are often needed in answering a clinical question. We explore a multi-document summarization approach to automatically find this information for questions about effects of using a … Cited by 25 Related articles All 45 versions
Statistical sentence extraction for information distillation D Hakkani-Tur, G Tur – Acoustics, Speech and Signal …, 2007 – ieeexplore.ieee.org ABSTRACT Information distillation aims to extract the most useful pieces of information related to a given query from massive, possibly multilingual, audio and textual document sources. One critical component in a distillation engine is detecting sentences to be … Cited by 21 Related articles All 14 versions
An effective sentence-extraction technique using contextual information and statistical approaches for text summarization Y Ko, J Seo – Pattern Recognition Letters, 2008 – Elsevier This paper proposes an effective method to extract salient sentences using contextual information and statistical approaches for text summarization. The proposed method combines two consecutive sentences into a bi-gram pseudo sentence so that contextual … Cited by 20 Related articles All 5 versions
Automatic summarization of mouse gene information by clustering and sentence extraction from MEDLINE abstracts J Yang, AM Cohen, W Hersh – AMIA Annual Symposium …, 2007 – ncbi.nlm.nih.gov Abstract Tools to automatically summarize gene information from the literature have the potential to help genomics researchers better interpret gene expression data and investigate biological pathways. The task of finding information on sets of genes is common for … Cited by 20 Related articles All 7 versions
Opinion summarization with integer linear programming formulation for sentence extraction and ordering H Nishikawa, T Hasegawa, Y Matsuo… – Proceedings of the 23rd …, 2010 – dl.acm.org Abstract In this paper we propose a novel algorithm for opinion summarization that takes account of content and coherence, simultaneously. We consider a summary as a sequence of sentences and directly acquire the optimum sequence from multiple review documents … Cited by 21 Related articles All 6 versions
Automatic document summarization by sentence extraction RM Aliguliyev – ?????????????? ??????????, 2007 – ict.nsc.ru
Information-content based sentence extraction for text summarization D Mallett, J Elding… – … Technology: Coding and …, 2004 – ieeexplore.ieee.org Abstract This paper proposes the FULL-COVERAGE summarizer: an efficient, information retrieval oriented method to extract non-redundant sentences from text for summarization purposes. Our method leverages existing Information Retrieval technology by extracting … Cited by 14 Related articles All 6 versions
Interactive relevance feedback with graded relevance and sentence extraction: simulated user experiments K Järvelin – Proceedings of the 18th ACM conference on …, 2009 – dl.acm.org Abstract Research on relevance feedback (RFB) in information retrieval (IR) has given mixed results. Success in RFB seems to depend on the searcher’s willingness to provide feedback and ability to identify relevant documents or query keys. The paper is based on … Cited by 14 Related articles All 6 versions
Summarising text with a genetic algorithm-based sentence extraction V Qazvinian, LS Hassanabadi… – International Journal of …, 2008 – Inderscience Automatic text summarisation has long been studied and used. The growth in the amount of information on the web results in more demands for automatic methods for text summarisation. Designing a system to produce human-quality summaries is difficult and … Cited by 13 Related articles All 6 versions
Fuzzy-rough set aided sentence extraction summarization HH Huang, YH Kuo, HC Yang – … Computing, Information and …, 2006 – ieeexplore.ieee.org Abstract In this paper, a novel method is proposed to extract key sentences of a document as its summary by estimating the relevance of sentences through the use of fuzzy-rough sets. This method uses senses rather than raw words to lessen the problem that sentences of … Cited by 14 Related articles All 5 versions
Text summarization by sentence extraction and syntactic pruning M Gagnon, L Da Sylva – 2005 – papyrus.bib.umontreal.ca Nous présentons une méthode hybride pour le résumé de texte, en combinant l’extraction de phrases et l’élagage syntaxique des phrases extraites. L’élagage syntaxique est effectué sur la base d’une analyse complète des phrases selon un parseur de dépendances, … Cited by 11 Related articles All 4 versions
Evaluation measures considering sentence concatenation for automatic summarization by sentence or word extraction C Hori, T Hirao, H Isozaki – Proceedings of Workshop on Text …, 2004 – aclweb.org … precision or accuracy. Although sentence extraction has previously been evaluated based only on precision of a single sentence, sentence concate- nations in the summaries should be evaluated as well. We have evaluated … Cited by 10 Related articles All 7 versions
Patient status classification by using rule based sentence extraction and BM25 kNN-based classifier E Aramaki, T Imai, K Miyo, K Ohe – i2b2 Workshop on Challenges in …, 2006 – luululu.com Abstract A method for classifying the status of a patient in a medical record is highly desired because this enables larger-scale statistical medical studies. The present paper introduces a system that classifies the smoking status a patient from a medical record. The system … Cited by 9 Related articles All 4 versions
Text Summarization by Sentence Extraction Using Unsupervised Learning RA García-Hernández, R Montiel, Y Ledeneva… – MICAI 2008: Advances …, 2008 – Springer Abstract The main problem for generating an extractive automatic text summary is to detect the most relevant information in the source document. Although, some approaches claim being domain and language independent, they use high dependence knowledge like key- … Cited by 10 Related articles All 14 versions
Automatic text summarization using two-step sentence extraction W Jung, Y Ko, J Seo – Information Retrieval Technology, 2005 – Springer Abstract Automatic text summarization sets the goal at reducing the size of a document while preserving its content. Our summarization system is based on Two-step Sentence Extraction. As it combines statistical methods and reduces noise data through two steps efficiently, it … Cited by 9 Related articles All 9 versions
Sentence extraction using time features in multi-document summarization JM Lim, IS Kang, JHJ Bae, JH Lee – Information Retrieval Technology, 2005 – Springer Abstract In multi-document summarization (MDS), especially for time-dependent documents, humans tend to select sentences in time sequence. Based on this insight, we use time features to separate documents and assign scores to sentences to determine the most … Cited by 9 Related articles All 8 versions
Multi-document summarisation using genetic algorithm-based sentence extraction A Kogilavani, P Balasubramanie – International Journal of Computer …, 2011 – Inderscience Automatic document summarisation is the process of generating a summary of the original documents with the aim of shorter reading time. Sentence extraction is a widely adopted document summarisation technique by which relevant sentences are extracted from … Cited by 8 Related articles All 4 versions
Sentence extraction-based automatic speech summarization and evaluation techniques S Furui, M Hirohata, Y Shinnaka… – Symposium on Large- …, 2005 – t2r2.star.titech.ac.jp ABSTRACT Tliis paper presents automatic speech summarization techniques and its evaluation metrics, focusing on sentence extraction-based summarization methods for making abstracts from spontaneous presentations. Since humans tend to summarize … Cited by 7 Related articles All 2 versions
Towards multi-lingual summarization: A comparative analysis of sentence extraction methods on English and Hebrew corpora M Litvak, H Lipman, AB Gur, M Last… – Proceedings of the 4th …, 2010 – aclweb.org Abstract The trend toward the growing multilinguality of the Internet requires text summarization techniques that work equally well in multiple languages. Only some of the automated summarization methods proposed in the literature, however, can be defined as … Cited by 8 Related articles All 13 versions
Medical textbook summarization and guided navigation using statistical sentence extraction G Whalen – AMIA Annual Symposium Proceedings, 2005 – ncbi.nlm.nih.gov Abstract We present a method for automated medical textbook and encyclopedia summarization. Using statistical sentence extraction and semantic relationships, we extract sentences from text returned as part of an existing textbook search (similar to a book index … Cited by 7 Related articles All 7 versions
HTML text segmentation for web page summarization by a key sentence extraction method W Sunayama, A Iyama… – Systems and Computers in …, 2006 – Wiley Online Library Abstract The information displayed as the search result by search engines is important for quickly finding the desired information. In particular, the summary of each Web page in the search results is important for determining the Web page content, as well as for … Cited by 6 Related articles All 3 versions
A formal model for information selection in multi-sentence text extraction E Filatova, V Hatzivassiloglou – … of the 20th international conference on …, 2004 – dl.acm.org … Simone Teufel and Marc Moens. 1997. Sentence extraction as a classification task. In Proceedings of the ACL/EACL 1997 Workshop on Intelligent Scalable Text Summarizaion, Spain. Ellen M. Voorhees. 2003. Evaluating answers to definition questions. … Cited by 59 Related articles All 12 versions
Automatic example sentence extraction for a contemporary German dictionary J Didakowski, L Lemnitzer, A Geyken – Proceedings EURALEX, 2012 – euralex.org Abstract The integration of illustrative examples into monolingual dictionaries provides an intuitive means for grasping the meaning of a word. Tight space constraints of print media no longer apply with online dictionaries. Thus, the inclusion of examples is obviously a useful … Cited by 5 Related articles
Cross-lingual sentence extraction for information distillation. AK Singla, DZ Hakkani-Tür – INTERSPEECH, 2008 – 20.210-193-52.unknown.qala.com. … Abstract Information distillation aims to analyze and interpret large volumes of speech and text archives in multiple languages and produce structured information of interest to the user. In this work, we investigate cross-lingual information distillation, where non-English ( … Cited by 5 Related articles All 3 versions
A Novel Chinese Multi-Document Summarization Using Clustering Based Sentence Extraction DX Liu, YX He, DH Ji, H Yang – Machine Learning and …, 2006 – ieeexplore.ieee.org Abstract: This paper proposes a strategy for Chinese multi-document summarization based on clustering and sentence extraction. It adopts the term vector to represent the linguistic unit in Chinese document, which obtains higher representation quality than traditional word- … Cited by 4 Related articles All 3 versions
Finding relevant features for Korean comparative sentence extraction S Yang, Y Ko – Pattern Recognition Letters, 2011 – Elsevier In this paper, we study how to extract comparative sentences from Korean text documents. We decompose our task into three steps:(1) collecting comparative keywords;(2) extracting comparative-sentence candidates by keyword searching; and (3) eliminating non- … Cited by 4 Related articles All 6 versions
iSpreadRank: Ranking sentences for extraction-based summarization using feature weight propagation in the sentence similarity network JY Yeh, HR Ke, WP Yang – Expert Systems with Applications, 2008 – Elsevier Sentence extraction is a widely adopted text summarization technique where the most important sentences are extracted from document(s) and presented as a summar. … Cited by 24 Related articles All 8 versions
Language Independent Sentence Extraction Based Text Summarization K Perumal, BB Chaudhuri – Proceedings of ICON-2011: 9th …, 2011 – sites.google.com Abstract This paper discusses an efficient language independent approach for the automated summarization of single documents based on sentence extraction. The proposed approach involves the use of a structural characteristics based sentence scoring along … Cited by 3 Related articles
Feature-Based Sentence Extraction Using Fuzzy Inference rules L Suanmali, N Salim… – … Conference on Signal …, 2009 – ieeexplore.ieee.org Abstract—Automatic text summarization is a wide research area. Automatic text summarization is to compress the original text into a shorter version and help the user to quickly understand large volumes of information. There are several ways in which one can … Cited by 5 Related articles All 5 versions
[BOOK] Sentence extraction by graph neural networks D Muratore, M Hagenbuchner, F Scarselli, AC Tsoi – 2010 – Springer Abstract In this paper, we will apply a recently proposed connectionist model, namely, the Graph Neural Network, for processing the graph formed by considering each sentence in a document as a node and the relationship between two sentences as an edge. Using … Cited by 3 Related articles All 4 versions
Genetic algorithm based sentence extraction for text summarization L Suanmali, N Salim, MS Binwahlan – International Journal of …, 2011 – kp.fsksm.utm.my Abstract The goal of text summarization is to generate summary of the original text that helps the user to quickly understand large volumes of information available in that text. This paper focuses on text summarization based on sentence extraction. One of the methods to … Cited by 3 Related articles All 5 versions
Significant sentence extraction by euclidean distance based on singular value decomposition C Lee, H Park, C Ock – Natural Language Processing–IJCNLP 2005, 2005 – Springer Abstract This paper describes an automatic summarization approach that constructs a summary by extracting the significant sentences. The approach takes advantage of the cooccurrence relationships between terms only in the document. The techniques used are … Cited by 4 Related articles All 9 versions
A simple sentence-level extraction algorithm for comparable data C Tillmann, J Xu – Proceedings of Human Language Technologies: The …, 2009 – dl.acm.org … Likewise, source word coverage can be decided by a simple array look-up. 3 Experiments The parallel sentence extraction algorithm presented in this paper is tested in detail on the large- scale Spanish-English Gigaword data (Graff, 2006; Graff, 2007). … Cited by 11 Related articles All 6 versions
Sentence extraction with support vector machine ensemble LN Minh, A Shimazu, HP Xuan, BH Tu, S Horiguchi – 2005 – dspace.jaist.ac.jp ??: This paper addresses a support vector machine model for text summarization problem. First, we formulate the text summarization problem as the problem of extracting a set of importance sentences. We then employ a support vector model for sloving that problem. … Cited by 2 Related articles All 2 versions
Topic Sentence Extraction Method Based on Weight Fuzzy Clustering and Mutual Information [J] K XUE, S YUAN, X ZHANG – Computer Engineering, 2009 – en.cnki.com.cn A topic sentence extraction method based on Weight Fuzzy Clustering (WFC) and Mutual Information (MI) is proposed, which is to cover more topics and lower the redundant information of the text. The abstract efficiency is promoted. Using WFC method, the … Cited by 2 Related articles
A Graph-Based Approach for Sentiment Sentence Extraction K Shimada, D Hashimoto, T Endo – New Frontiers in Applied Data Mining, 2009 – Springer Abstract As the World Wide Web rapidly grows, a huge number of online documents are easily accessible on the Web. We obtain a huge number of review documents that include user’s opinions for products. To classify the opinions is one of the hottest topics in natural … Cited by 2 Related articles All 8 versions
A New method for Vietnamese Sentence Extraction based on important information of topic word and linguistic score HNT Thu, QN Huu – … of 2010 2nd International Conference on …, 2010 – cpfd.cnki.com.cn [??]: This article presented a new method for calculation of Vietnamese sentence weight based on information significant and linguistic score. In our method, two sets of words are extracted from sentence. A set of word indicate information in sentence, and other set of … Cited by 2 Related articles
A Novel Chinese Text Summarization Approach Using Sentence Extraction Based on Kernel Words Recognition W Yang, R Dai, X Cui – Fuzzy Systems and Knowledge …, 2008 – ieeexplore.ieee.org Abstract The continuing growth of World Wide Web and on-line text collections makes a large volume of information available to users. Automatic text summarization helps users to quickly understand the documents. This paper proposes an automated technique for … Cited by 2 Related articles All 5 versions
Text summarization with harmony search algorithm-based sentence extraction E Shareghi, LS Hassanabadi – … of the 5th international conference on …, 2008 – dl.acm.org Abstract Currently vast amounts of textual information exist in large repositories such as Web. To processes such a huge amount of information, automatic text summarization has been of great interests. Unlike many approaches which focus on sentence or paragraph … Cited by 2 Related articles
Bag of senses versus bag of words: comparing semantic and lexical approaches on sentence extraction JG Flores, L Gillard, O Ferret, G de Chandelar – TAC 2008 Workshop- …, 2008 – nist.gov Abstract Sentence extraction is a valuable technique for automatic summarization. This paper presents LIC2M’s first participation in TAC evaluation campaign (update summarization task). We describe two main extractive approaches for summarization. The … Cited by 2 Related articles All 3 versions
Iterative sentence-pair extraction from quasi-parallel corpora for machine translation. R Sarikaya, S Maskey, R Zhang… – …, 2009 – 20.210-193-52.unknown.qala.com. … … PARALLEL SEED DATA ENGLISH SPANISH BUILD SMT MODELS Figure 1: Flow Chart for Iterative Sentence Extraction Method. 2.3. Context Extrapolation The context extrapolation is one of the key steps that makes our algorithm different than others. … Cited by 7 Related articles All 8 versions
Answer Sentence Extraction of Reading Comprehension Based on Shallow Semantic Tree Kernel [J] Z ZHANG, Y ZHANG, T LIU, S LI – Journal of Chinese Information …, 2008 – en.cnki.com.cn Automatic reading comprehension systems can analyze a given passage and generate/extract answers in response to questions about the passage. An approach integrating shallow semantic information to extract answer sentence is proposed in this … Cited by 1 Related articles
A Novel Application of Fuzzy Set Theory and Topic Model in Sentence Extraction for Vietnamese Text HNT Thu, NT Luan – … Journal of Computer Science and Network …, 2010 – paper.ijcsns.org Summary Vietnamese language has common characteristics with some Asian languages such as Chinese, Japanese, Korean… They do not define words based on spaces. In this article, we present a method that application of Fuzzy set theory and topic model to extract … Cited by 1 Related articles All 2 versions
Chinese–japanese parallel sentence extraction from quasi–comparable corpora C Chu, T Nakazawa, S Kurohashi – ACL 2013, 2013 – aclweb.org Abstract Parallel sentences are crucial for statistical machine translation (SMT). However, they are quite scarce for most language pairs, such as Chinese–Japanese. Many studies have been conducted on extracting parallel sentences from noisy parallel or comparable … Cited by 1 Related articles All 5 versions
Multi-document summarization based on rhetorical structure: Sentence extraction and evaluation X Yong-dong, W Xiao-long, L Tao… – Systems, Man and …, 2007 – ieeexplore.ieee.org Abstract—A Multi-document Rhetorical Structure (MRS) is proposed for multi-document automatic summarization task. This structure can represent interrelationship between text units at different levels of granularity and can describe simultaneously the happen and … Cited by 1 Related articles All 3 versions
Sentence Extraction Using Asymmetric Word Similarity and Topic Similarity M Azmi-Murad, TP Martin – Applied Soft Computing Technologies: The …, 2006 – Springer Abstract We propose a text summarization system known as MySum in finding the significance of sentences in order to produce a summary based on asymmetric word similarity and topic similarity. We use mass assignment theory to compute similarity … Cited by 1 Related articles All 2 versions
Summarization by Latent Dirichlet Allocation: Superior Sentence Extraction through Topic Modeling KW Murray – A senior thesis for Bachelors degree, Princeton …, 2009 – kentonmurray.com A Senior Thesis submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of a Bachelors of Science in Engineering … This Thesis represents my own work in accordance with University Regulations. … I would like to thank my family … Cited by 1 Related articles All 2 versions
Free Model of Sentence Classifier for Automatic Extraction of Topic Sentences ML Khodra, DH Widyantoro, EA Aziz… – Journal of ICT …, 2011 – journals.itb.ac.id … For each feature vector, the system calculates the probability of topic sentence assignment. Figure 1 Corpus-based classification system in two phases: model development, topic sentence extraction. … classification Model Development Topic sentence Extraction Preprocessing … Cited by 1 Related articles All 9 versions
A novel approach for research paper abstracts summarization using cluster based sentence extraction SR Patil, SM Mahajan – Proceedings of the International Conference & …, 2011 – dl.acm.org Abstract This paper presents a part of research work to develop a method for automatic summarization of sets of research paper abstracts of desired subject in a specific area that may be retrieved by a digital library system or search engine in response to a user query. … Related articles
Opinion sentence and topic relevant sentence extraction by using coherent structure among the sentences HMMTKT DaiKusui – research.nii.ac.jp Abstract We developed a new sentence extraction framework, the Sliding Window Framework, by using coherent structure among the sentences. Coherent structure means that the sentences that relate to a certain topic in an article are written in clusters to … Related articles All 2 versions
Sub-sentence extraction based on combinatorial optimization N Yasuda, M Nishino, T Hirao, M Nagata – Advances in Information …, 2013 – Springer Abstract This paper describes the prospect of word extraction for text summarization based on combinatorial optimization. Instead of the commonly used sentence-based approach, word-based approaches are preferable if highly-compressed summarizations are required … Related articles All 2 versions
Opinion Sentence Extraction and Sentiment Analysis for Chinese Microblogs H Shi, W Chen, X Li – Natural Language Processing and Chinese …, 2013 – Springer Abstract Sentiment analysis of Chinese microblogs is important for scientific research in public opinion supervision, personalized recommendation and social computing. By studying the evaluation task of NLP&CC’2012, we mainly implement two tasks, namely the … Related articles All 3 versions
Exploring simultaneous keyword and key sentence extraction: improve graph-based ranking using wikipedia X Wang, L Wang, J Li, S Li – Proceedings of the 21st ACM international …, 2012 – dl.acm.org Abstract Summarization and Keyword Selection are two important tasks in NLP community. Although both aim to summarize the source articles, they are usually treated separately by using sentences or words. In this paper, we propose a two-level graph based ranking … Related articles
Opinion summarisation through sentence extraction: an investigation with movie reviews M Bonzanini, M Martinez-Alvarez… – Proceedings of the 35th …, 2012 – dl.acm.org Abstract In on-line reviews, authors often use a short passage to describe the overall feeling about a product or a service. A review as a whole can mention many details not in line with the overall feeling, so capturing this key passage is important to understand the overall … Related articles All 2 versions
Syntactico-Semantic Analysis: A Hybrid Sentence Extraction Strategy for Automatic Summarization JG Flores, G de Chalendar – Artificial Intelligence, 2008. MICAI’ …, 2008 – ieeexplore.ieee.org Abstract Automatic summarization systems often make use of sentence extraction methods to select significant content in texts. This paper presents two sentence extraction strategies. The first one is based on a semantic analysis using word senses built by means of a … Related articles All 5 versions
The Method of Chinese Opinion Sentence Extraction and Polarity Identification Based on Sentimental Elements N Liu, YX He, FY He, M Peng, JB Liu – Advanced Materials …, 2013 – Trans Tech Publ Page 1. The Method of Chinese Opinion Sentence Extraction and Polarity Identification Based on Sentimental Elements … Keywords: Text Sentiment Analysis; Opinion Sentence Extraction; Polarity Identification; Sentimental Element Abstract. … Related articles
Effective Chinese Relation Extraction by Sentence Rolling and Candidate Ranking M Sheng, L Qiu, C Wu, H Wang, Y Yu – Linked Data and Knowledge …, 2013 – Springer … 4.3 Evaluation of Key Sentence Extraction … It’s important to en- sure that the real informative sentences have high sentence scores calculated by Formula 4. Corpus 2 is used to evaluate the performance of the key sentence extraction in this section. … Related articles All 2 versions
Chinese Subjective Sentence Extraction Based on Dictionary and Combination Classifiers W Chen, Y Zhou, X Wang – Physics Procedia, 2011 – Elsevier For extracting of Chinese subjective sentence, this paper proposes a new dictionary-based extraction method and a novel classifier combination strategy. For the first method, we use the training data to score the subjective dictionary, which was composed of indicative verb … Related articles All 3 versions
Gene Ontology Evdience Sentence Extraction and Concept Extraction: Two Rule-Based Approaches YD Chen, CJ Yang, WG Li, CY Huang, JH Chiang – 2013 – biocreative.org Abstract Gene Ontology (GO) annotation have been relying on human annotation to capture accurate description of the published full-length literature. Though manual annotation may provide promising quality of the task. However, it is labour-intensive and time-consuming. … All 3 versions
Test of complementarity on sentence extraction methods AB Moro, JJL Martinez, HJ Salazar – Impresos de Inscripción, 2008 – sepln.org Abstract: In this work three approaches to sentence extraction methods are analyzed. We try to find if the used methods show some complementary features. In order to accomplish this goal, the methods of sentence extraction were applied and combined, analyzing the … Related articles All 11 versions
Important Sentence Extraction Using Contextual Semantic Network J Okamoto, S Ishizaki – Procedia-Social and Behavioral Sciences, 2011 – Elsevier In this paper, we propose a method for calculating important scores of sentences for text summarization. In this method, Contextual Semantic Network is used to calculate scores of importance for sentences included in input documents. The Contextual Semantic Network … Related articles
Research on Sentence Extraction in Text Summarization L ZHANG, H WANG – Journal of Chinese Information Processing, 2012 – en.cnki.com.cn Extractive summarization attempts to extract important sentences from the original text and re-organize them in a summary. In this paper we propose a method to automatically identify significant sentences. The basic idea of this method is to label each sentence with one of …
Statistical Sentence Extraction for Multilingual Information Distillation A Singla, S Yaman – icsi.berkeley.edu Abstract Information distillation aims to assist an analyst by extracting the most useful pieces of information related to a given query from massive, possibly multilingual, audio and textual document sources. Finding sentences that are relevant answers to the user’s query from … Related articles All 2 versions
Text Summarization Method Applying Vocabulary Combination into Sentence Extraction W Yongqing, J Peipei, X Mingying – International Journal of Advancements …, 2011 – aicit.org Abstract Semantic loss between feature words is identified as the main reason for the low quality of text summary, however, the root reason for this phenomenon is the low segmentation accuracy of lexical analysis system and the orthogonal assumptions existed … Related articles
Similarity measures and diversity rankings for query-focused sentence extraction P Achananuparp – 2010 – idea.library.drexel.edu Query-focused sentence extraction generally refers to an extractive approach to select a set of sentences that responds to a specific information need. It is one of the major approaches employed in multi-document summarization, focused summarization, and complex … Related articles All 6 versions
MRS for multi-document summarization by sentence extraction YD Xu, XD Zhang, GR Quan, YD Wang – Telecommunication Systems, 2013 – Springer Abstract A Multi-document Rhetorical Structure (MRS) is proposed for multi-document automatic summarization task. In this structure, interrelationship between text units, including the correlation between units calculated by hierarchical topic tree, the rhetorical … Related articles All 3 versions
Two-Step Sentence Extraction for Summarization of Meeting Minutes JK Lee, HJ Song, SB Park – Information Technology: New …, 2011 – ieeexplore.ieee.org Abstract—These days a number of meeting minutes of various organizations are publicly available and the interest in these documents by people is increasing. However it is time- consuming and tedious to read and understand whole documents even if the documents … Cited by 1 Related articles All 4 versions
Sentence extraction for legal text summarisation B Hachey, C Grover – INTERNATIONAL JOINT CONFERENCE ON …, 2005 – ijcai.org Abstract We describe a system for generating extractive summaries of texts in the legal domain, focusing on the relevance classifier, which determines which sentences are abstract-worthy. We experiment with naive Bayes and maximum entropy estimation … Related articles All 12 versions
Evidence Based Approach for Sentence Extraction from Single Documents S Manna, T Gedeon, BSU Mendis… – Acta Technica Jaurinensis, 2009 – acta.sze.hu Abstract We present an evidence based sentence extraction model which is an application of subjective logic in a document computing scenario, to rank sentences according to their írnportanec in a document. Elements from the Dempster-Shafer belief theory arc used by … Related articles
Visualizing the LAK/EDM literature using combined concept and rhetorical sentence extraction D Taibi, Á Sándor, D Simsek, S Buckingham Shum… – 2013 – oro.open.ac.uk Scientific communication demands more than the mere listing of empirical findings or assertion of beliefs. Arguments must be constructed to motivate problems, expose weaknesses, justify higher-order concepts, and support claims to be advancing the field. … Related articles All 3 versions
A combined method of text summarization via sentence extraction C Dang, X Luo – Proceedings of the 2007 annual Conference on …, 2007 – wseas.us Abstract:-In this paper, we propose a practical approach for extracting the most relevant sentences from the original document to form a summary. We present this summarization procedure based upon statistical selection and WordNet. Experimental results show that … Related articles All 2 versions
Sentence extraction with topic modeling for question–answer pair generation CH Wu, CH Liu, PH Su – Soft Computing, 2014 – Springer Abstract Recently, automatic QA pair generation has been an essential technique to reduce human involvement in the construction of QA systems. In a big data era, huge information is produced every day. Therefore, it is an important issue for QA systems to be able to …
HTML Text Segmentation For Web Page Summarization By A Key Sentence Extraction Method M Artis, A Beyer – Systems and Computers in Japan, 2006 – lw20.com Abstract: The information displayed as the search result by search engines is important for quickly finding the desired information. In particular, the summary of each Web page in the search results is important for determining the Web page content, as well as for …
Sentence Extraction F Scarselli, M Hagenbuchner, D Muratore – alpha.ing.unisi.it The increasing of the textual resources available online has raised, in the past last years, the need of improving the access to textual information. Information retrieval engines, text summarisers, question answering systems, and language translators have been … Related articles All 7 versions
AMDS: Sentence Extraction Based Proficient Framework for Multi-Document Summarization C Balasubramanian, KG Srinivasagan… – The International …, 2013 – atlantis-press.com Abstract:-Rapid improvement of electronic documents in World Wide Web has made overload to the users in accessing the information. Therefore, abstracting the primary content from numerous documents related to same topic is highly essential. … Related articles All 2 versions
Sentence Compression for Target-Polarity Word Collocation Extraction Y Zhao, W Che, H Guo, B Qin, Z Su, T Liu – anthology.aclweb.org … Kevin Knight and Daniel Marcu. 2002. Summarization beyond sentence extraction: A probabilistic approach to sentence compression. Artif. Intell., 139(1):91–107, July. Terry Koo, Xavier Carreras, and Michael Collins. 2008. Simple semi-supervised dependency parsing. …
Coordinate relationship extraction on sentence level in Chinese corpus R Sun, Z Liu, W Zhou – Natural Computation (ICNC), 2013 Ninth …, 2013 – ieeexplore.ieee.org Page 1. 978-1-4673-4714-3/13/$31.00 ©2013 IEEE 127 2013 Ninth International Conference on Natural Computation (ICNC) Coordinate Relationship Extraction On Sentence Level In Chinese Corpus Rong Sun School of Computer … Related articles
Chinese Standard Comparative Sentence Recognition and Extraction Research L Xing, L Liu – Proceedings of the International Conference on …, 2013 – Springer … Based on the data, we process comparative sentence extraction and classification of the standard document to receive specific categories of documents by defining feature vocabulary and synonyms. The data set is shown in Table 52.3. Table 52.3 Samples of data set. … Related articles All 2 versions
A Holistic Approach to Bilingual Sentence Fragment Extraction from Comparable Corpora. M Khademian, K Taghipour, S Mansour, S Khadivi – LREC, 2012 – lrec-conf.org … language titles of the same documents. By applying the created lexicon and similarity measure, paral- lel sentences are extracted. (Smith et al., 2010) trained a ranking model for sentence extraction. It uses some fea- tures such … Related articles All 5 versions