Extractive Summarization


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100 Best GitHub: Automatic Summarization | Abstractive Summarization 2013 | Automatic Summarization | Automatic Summarization & Dialog Systems 2011 | Automatic Summarization 2011 | Automatic Summarization 2012 | Automatic Summarization 2013 | Sentence Summarization | Summarization Systems


Graph-based submodular selection for extractive summarization H Lin, J Bilmes, S Xie – … , 2009. ASRU 2009. IEEE Workshop on, 2009 – ieeexplore.ieee.org Abstract—We propose a novel approach for unsupervised extractive summarization. Our approach builds a semantic graph for the document to be summarized. Summary extraction is then formulated as optimizing submodular functions defined on the semantic graph. The … Cited by 26 Related articles All 15 versions

Discovery of topically coherent sentences for extractive summarization A Celikyilmaz, D Hakkani-Tür – Proceedings of the 49th Annual Meeting …, 2011 – dl.acm.org Abstract Extractive methods for multi-document summarization are mainly governed by information overlap, coherence, and content constraints. We present an unsupervised probabilistic approach to model the hidden abstract concepts across documents as well … Cited by 22 Related articles All 8 versions

Using the Amazon Mechanical Turk to transcribe and annotate meeting speech for extractive summarization M Marge, S Banerjee, AI Rudnicky – … of the NAACL HLT 2010 Workshop …, 2010 – dl.acm.org Abstract Due to its complexity, meeting speech provides a challenge for both transcription and annotation. While Amazon’s Mechanical Turk (MTurk) has been shown to produce good results for some types of speech, its suitability for transcription and annotation of … Cited by 17 Related articles All 4 versions

Using N-best recognition output for extractive summarization and keyword extraction in meeting speech Y Liu, S Xie, F Liu – Acoustics Speech and Signal Processing ( …, 2010 – ieeexplore.ieee.org ABSTRACT There has been increasing interest recently in meeting understanding, such as summarization, browsing, action item detection, and topic segmentation. However, there is very limited effort on using rich recognition output (eg, recognition confidence measure or … Cited by 15 Related articles All 3 versions

Evolutionary algorithm for extractive text summarization R Alguliev, R Aliguliyev – Intelligent Information Management, 2009 – file.scirp.org There are two types of summarization: extractive and abstractive. Extractive summarization methods simplify the problem of summarization into the problem of selecting a representative subset of the sentences in the original documents. … Cited by 16 Related articles All 5 versions

A risk minimization framework for extractive speech summarization SH Lin, B Chen – Proceedings of the 48th annual meeting of the …, 2010 – dl.acm.org … In this paper, we formulate extractive summarization as a risk minimization problem and propose a unified probabilis- tic framework that naturally combines su- pervised and unsupervised summarization models to inherit their individual merits as well as to overcome their … Cited by 15 Related articles All 7 versions

Quantifying the limits and success of extractive summarization systems across domains H Ceylan, R Mihalcea, U Özertem, E Lloret… – … : The 2010 Annual …, 2010 – dl.acm.org Abstract This paper analyzes the topic identification stage of single-document automatic text summarization across four different domains, consisting of newswire, literary, scientific and legal documents. We present a study that explores the summary space of each domain via … Cited by 11 Related articles All 6 versions

Fuzzy evolutionary optimization modeling and its applications to unsupervised categorization and extractive summarization W Song, L Cheon Choi, S Cheol Park… – Expert Systems with …, 2011 – Elsevier Modern information retrieval (IR) systems consist of many challenging components, eg clustering, summarization, etc. Nowadays, without browsing the whole volume of datasets, IR systems present users with clusters of documents they are interested in, and … Cited by 12 Related articles All 7 versions

A survey of text summarization extractive techniques V Gupta, GS Lehal – Journal of Emerging Technologies in …, 2010 – academypublisher.com … An extractive summarization method consists of selecting important sentences, paragraphs etc. from the original document and concatenating them into shorter form. … An extractive summarization method consists of selecting important sentences, paragraphs etc. … Cited by 97 Related articles All 12 versions

Automatic Punjabi Text Extractive Summarization System. V Gupta, GS Lehal – COLING (Demos), 2012 – kde.cs.tut.ac.jp ABSTRACT Text Summarization is condensing the source text into shorter form and retaining its information content and overall meaning. Punjabi text Summarization system is text extraction based summarization system which is used to summarize the Punjabi text … Cited by 10 Related articles All 2 versions

Company-oriented extractive summarization of financial news K Filippova, M Surdeanu, M Ciaramita… – Proceedings of the 12th …, 2009 – dl.acm.org Abstract The paper presents a multi-document summarization system which builds company- specific summaries from a collection of financial news such that the extracted sentences contain novel and relevant information about the corresponding organization. The user’s … Cited by 10 Related articles All 13 versions

A new sentence similarity measure and sentence based extractive technique for automatic text summarization RM Aliguliyev – Expert Systems with Applications, 2009 – Elsevier … We propose the generic document summarization method which is based on sentence clustering. The proposed approach is a continue sentence-clustering based extractive summarization methods, proposed in Alguliev [Alguliev, RM, Aliguliyev, RM, Bagirov, AM (2005). … Cited by 78 Related articles All 3 versions

Semi-supervised extractive speech summarization via co-training algorithm. S Xie, H Lin, Y Liu – INTERSPEECH, 2010 – 20.210-193-52.unknown.qala.com. … … In this paper, we investigate extractive summarization, in which the most representative segments from the original doc- ument are selected and concatenated together to form a final summary. … 3. Supervised Extractive Summarization … Cited by 7 Related articles All 12 versions

Extractive speech summarization-from the view of decision theory. SH Lin, YM Yeh, B Chen – INTERSPEECH, 2010 – 20.210-193-52.unknown.qala.com. … … Although we have described a general formulation for the extractive summarization problem on the grounds of the Bayes decision theory in this section, we consider hereafter two special cases of it where the selection strategy is implemented in either a “sentence-wise” manner … Cited by 6 Related articles All 2 versions

Extractive speech summarization by active learning JJ Zhang, RHY Chan, P Fung – Automatic Speech Recognition …, 2009 – ieeexplore.ieee.org … Active Learning Justin Jian Zhang, Ricky Ho Yin Chan, Pascale Fung {pascale, zjustin}@ece.ust.hk, ricky@cs.ust.hk Abstract—In this paper, we propose an active learning ap- proach for feature-based extractive summarization of lecture speech. … Cited by 6 Related articles

Aspect-based extractive summarization of online reviews X Xu, T Meng, X Cheng – Proceedings of the 2011 ACM Symposium on …, 2011 – dl.acm.org Abstract In this paper, we study the aspect-based extractive summarization based on the observations that a good summary should present representative opinions on user concerned sub-aspects within limited words. According to these observations, we argue … Cited by 6 Related articles

Extractive summarization using complex networks and syntactic dependency DR Amancio, MGV Nunes, ON Oliveira Jr… – Physica A: Statistical …, 2012 – Elsevier The realization that statistical physics methods can be applied to analyze written texts represented as complex networks has led to several developments in natural language processing, including automatic summarization and evaluation of machine translation. … Cited by 7 Related articles All 9 versions

Wikisent: weakly supervised sentiment analysis through extractive summarization with wikipedia S Mukherjee, P Bhattacharyya – Machine Learning and Knowledge …, 2012 – Springer Abstract This paper describes a weakly supervised system for sentiment analysis in the movie review domain. The objective is to classify a movie review into a polarity class, positive or negative, based on those sentences bearing opinion on the movie alone, … Cited by 6 Related articles All 12 versions

Hybrids of supervised and unsupervised models for extractive speech summarization. SH Lin, YT Lo, YM Yeh, B Chen – …, 2009 – 20.210-193-52.unknown.qala.com. … … Generally, the summarization techniques can be classified as either extractive or abstractive. Extractive summarization produces a summary by selecting salient sentences or paragraphs from an original document according to a predefined target summarization ratio. … Cited by 5 Related articles All 3 versions

Learning to model domain-specific utterance sequences for extractive summarization of contact center dialogues R Higashinaka, Y Minami, H Nishikawa… – Proceedings of the 23rd …, 2010 – dl.acm.org Abstract This paper proposes a novel extractive summarization method for contact center dialogues. We use a particular type of hidden Markov model (HMM) called Class Speaker HMM (CSHMM), which processes operator/caller utterance sequences of multiple … Cited by 5 Related articles All 7 versions

Automated extractive single-document summarization: beating the baselines with a new approach A Barrera, R Verma – Proceedings of the 2011 ACM Symposium on …, 2011 – dl.acm.org … ROUGE, which compares single document summaries to baselines. Keywords Automated summarization, extractive summarization, single- document summarization 1. INTRODUCTION Our current Internet-driven age brings … Cited by 6 Related articles

Integrating prosodic features in extractive meeting summarization S Xie, D Hakkani-Tur, B Favre… – … Speech Recognition & …, 2009 – ieeexplore.ieee.org … work. III. FEATURES FOR EXTRACTIVE MEETING SUMMARIZATION The extractive summarization task can be considered as a binary classification problem and solved using supervised learning approaches. Each training … Cited by 22 Related articles All 9 versions

Extractive speech summarization using shallow rhetorical structure modeling JJ Zhang, RHY Chan, P Fung – Audio, Speech, and Language …, 2010 – ieeexplore.ieee.org … Abstract We propose an extractive summarization approach with a novel shallow rhetorical structure learning framework for speech summarization. One of the most under-utilized features in extractive summarization … Cited by 20 Related articles All 4 versions

A probabilistic generative framework for extractive broadcast news speech summarization YT Chen, B Chen, HM Wang – Audio, Speech, and Language …, 2009 – ieeexplore.ieee.org … Abstract—In this paper, we consider extractive summarization of broadcast news speech and propose a unified probabilistic gen- erative framework that combines the sentence generative prob- ability and the sentence prior probability for sentence ranking. … Cited by 21 Related articles All 11 versions

Leveraging sentence weights in a concept-based optimization framework for extractive meeting summarization. S Xie, B Favre, D Hakkani-Tür, Y Liu – INTERSPEECH, 2009 – icsi.berkeley.edu … Index Terms: global optimization, sentence weights, meeting summarization 1. INTRODUCTION Extractive summarization selects salient sentences from the original documents (or recordings) and presents them as a sum- mary. … Cited by 17 Related articles All 11 versions

Extractive Summarization Based on Event Term Temporal Relation Graph and Critical Chain M Liu, W Li, H Hu – Information Retrieval Technology, 2009 – Springer Abstract In this paper, we investigate whether temporal relations among event terms can help improve event-based extractive summarization and text cohesion of machine- generated summaries. Using the verb semantic relation, namely happens-before provided … Cited by 3 Related articles All 5 versions

Significance of learner dependent features for improving text readability using extractive summarization K Nandhini, SR Balasundaram – Intelligent Human Computer …, 2012 – ieeexplore.ieee.org Abstract—Information and Communication Technologies play major role in all types of day to day life activities including Government, public and social domains. The need for HCI aspects to be taken care in these activities has become a predominant one. Especially, … Cited by 3 Related articles

Extractive summarization using a latent variable model. A Celikyilmaz, D Hakkani-Tür – INTERSPEECH, 2010 – 20.210-193-52.unknown.qala.com. … Abstract Extractive multi-document summarization is the task of choosing sentences from a set of documents to compose a summary text in response to a user query. We propose a generative approach to explicitly identify summary and non-summary topic distributions in … Cited by 3 Related articles All 2 versions

Learning deep rhetorical structure for extractive speech summarization JJ Zhang, P Fung – Acoustics Speech and Signal Processing ( …, 2010 – ieeexplore.ieee.org … ABSTRACT Extractive summarization of conference and lecture speech is useful for online learning and references. We show for the first time that deep(er) rhetorical parsing of conference speech is possible and helpful to extractive summarization task. … Cited by 2 Related articles All 4 versions

Complex networks and extractive summarization L Antiqueira, MGV Nunes – the Extended Activities Proceedings of the …, 2010 – inf.pucrs.br Abstract. Automatic summarization of texts is now crucial for several information retrieval tasks owing to the huge amount of information available in digital media, which has increased the demand for simple, language-independent extractive summarization … Cited by 2 Related articles

Single extractive text summarization based on a genetic algorithm RA García-Hernández, Y Ledeneva – Pattern Recognition, 2013 – Springer … summaries. Summarization methods can be classified into abstractive and extractive summarization. … omitted. An extractive summarization method only decides, for each sentence, whether or not it will be included in the summary. … Cited by 2 Related articles All 2 versions

Toward extractive summarization of multimodal documents P Wu, S Carberry – Proceedings of the Workshop on Text …, 2011 – cs.toronto.edu Abstract. Summarization research has focused on text, and relatively little attention has been given to the summarization of multimodal documents. If extractive summarization techniques are to be used on multimodal documents containing information graphics (bar charts, line … Cited by 2 Related articles All 5 versions

A fuzzy-rough hybrid approach to multi-document extractive summarization HH Huang, HC Yang, YH Kuo – Hybrid Intelligent Systems, …, 2009 – ieeexplore.ieee.org Abstract—To generate a multi-document extractive summary, the measurement of sentence relevance is of vital importance. Earlier work, exploring statistics of textual terms at the word (surface) level, faces the problem that the textual terms may be synonymous or … Cited by 2 Related articles All 5 versions

What is my essay really saying? Using extractive summarization to motivate reflection and redrafting. N Van Labeke, D Whitelock, D Field, S Pulman… – AIED …, 2013 – open.ac.uk ABSTRACT This paper reports on progress on the design of OpenEssayist, a web application that aims at supporting students in writing essays. The system uses techniques from Natural Language Processing to automatically extract summaries from free-text … Cited by 2 Related articles

SumCR: a new subtopic-based extractive approach for text summarization JP Mei, L Chen – Knowledge and information systems, 2012 – Springer … A summary is typically generated with two main categories of techniques, called extraction and abstraction [16,17,23]. Extractive summarization simply extracts salient information, such as sentences, from the input documents and “put them together” to form summaries. … Cited by 7 Related articles All 10 versions

Subtree Extractive Summarization via Submodular Maximization. H Morita, R Sasano, H Takamura, M Okumura – ACL (1), 2013 – aclweb.org Abstract This study proposes a text summarization model that simultaneously performs sentence extraction and compression. We translate the text summarization task into a problem of extracting a set of dependency subtrees in the document cluster. We also … Cited by 4 Related articles All 3 versions

Automatic extractive summarization on meeting corpus S Xie – 2010 – hlt.utdallas.edu This dissertation (or thesis) was produced in accordance with guidelines which permit the inclusion as part of the dissertation (or thesis) the text of an original paper or papers submitted for publication. The dissertation (or thesis) must still conform to all other … Cited by 2 Related articles All 3 versions

Combining syntax and semantics for automatic extractive single-document summarization A Barrera, R Verma – Computational Linguistics and Intelligent Text …, 2012 – Springer … sentences. Due to the complex linguistic and real-world knowledge required for truly abstrac- tive summaries, extractive summarization has become a more popular choice for computation and is the focus of this study. Although … Cited by 7 Related articles All 3 versions

An optimized dual classification system for Arabic extractive generic text summarization IMAH Sobh – 2009 – rdi-eg.com … today. Generally speaking, summaries could be extractive or abstractive. Extractive summarization extracts text by selecting from original document important … 2.2 Extractive summarizers Extractive summarization extracts text by selecting from original document … Cited by 8 Related articles All 7 versions

Extractive speech summarization using evaluation metric-related training criteria B Chen, SH Lin, YM Chang, JW Liu – Information Processing & …, 2013 – Elsevier … Much work on extractive summarization has been initiated for developing machine-learning approaches that usually cast important sentence selection as a two-class classification problem and have been applied with some success to a number of speech summarization tasks. … Cited by 6 Related articles All 7 versions

Active learning of extractive reference summaries for lecture speech summarization JJ Zhang, P Fung – Proceedings of the 2nd Workshop on Building and …, 2009 – dl.acm.org … Consequently, annotator agreement is low. Refer- ence summary generation is a tedious and low ef- ficiency task. On the other hand, supervised learn- ing of extractive summarization requires a large amount of training data of reference summaries. … Cited by 3 Related articles All 13 versions

[BOOK] Investigating the extractive summarization of literary novels H Ceylan, R Adviser-Mihalcea – 2011 – dl.acm.org Abstract Due to the vast amount of information we are faced with, summarization has become a critical necessity of everyday human life. Given that a large fraction of the electronic documents available online and elsewhere consist of short texts such as Web … Cited by 1 Related articles All 2 versions

Improved extractive summarization of Chinese texts using latent semantic analysis S Xiao, YX He – Application Research of Computers, 2012 – en.cnki.com.cn Chinese extractive summarization is a convenient method to realize Chinese text summarization, which extractes sentences and composites summarization corresponding to the extractive rules. This paper proposed an improved Chinese extractive summarization … Cited by 1 Related articles All 2 versions

Information Theoretic Approach To Extractive Text Summarization G Ravindra – 2009 – etd.ncsi.iisc.ernet.in … Keywords: Abstracting Collocation Method Information Theory Text Summarization Discrimination Threshold Dictionary Enhanced ESCI Extractive Summarization Using Collocation Information (ESCI) Dictionary Enhanced Fuzzy Summary Evaluator (DeFuSE) Collocation … Cited by 1 Related articles All 2 versions

Using Proximity in Query Focused Multi-document Extractive Summarization S Li, Y Zhang, W Wang, C Wang – Computer Processing of Oriental …, 2009 – Springer Abstract The query focused multi-document summarization tasks usually tend to answer the queries in the summary. In this paper, we suggest introducing an effective feature which can represent the relation of key terms in the query. Here, we adopt the feature of term … Cited by 1 Related articles All 5 versions

Toward a gold standard for extractive text summarization A Kennedy, S Szpakowicz – Advances in Artificial Intelligence, 2010 – Springer … The question arises just how good extractive summarization can ever be. … Starting from this cor- pus, we created SCU-optimal summaries for extractive summarization. We support the claim of optimality with a series of experiments. 1 Introduction … Cited by 1 Related articles All 9 versions

The role of statistical and semantic features in single-document extractive summarization T Vodolazova, E Lloret, R Muñoz… – Artificial Intelligence …, 2013 – sciedu.ca Abstract This paper reports on the further results of the ongoing research analyzing the impact of a range of commonly used statistical and semantic features in the context of extractive text summarization. The features experimented with include word frequency, … Cited by 1 Related articles All 4 versions

Improving hmm-based extractive summarization for multi-domain contact center dialogues R Higashinaka, Y Minami, H Nishikawa… – … (SLT), 2010 IEEE, 2010 – ieeexplore.ieee.org ABSTRACT This paper reports the improvements we made to our previously proposed hidden Markov model (HMM) based summarization method for multi-domain contact center dialogues. Since the method relied on Viterbi decoding for selecting utterances to include … Cited by 1 Related articles All 6 versions

Extractive summarization of development emails E Mastrodicasa – 2012 – inf.unisi.ch Abstract During the development of a project, programmers discuss problems, structural decisions, bugs, time management, etc. To do so, they use instant messaging, write on dedicated forums, and exchange emails that form threads that are also considered as a … Cited by 1 Related articles All 3 versions

Extractive summarization of personal photos from life events P Sinha, R Jain – Multimedia and Expo (ICME), 2011 IEEE …, 2011 – ieeexplore.ieee.org ABSTRACT Manually sifting through large collections of personal photos shot at various life events is both tedious and inefficient. In this paper, we propose a photo summarization system which creates a representative subset summary by extracting photos from a larger … Cited by 2 Related articles All 5 versions

Active learning with semi-automatic annotation for extractive speech summarization JJ Zhang, P Fung – ACM Transactions on Speech and Language …, 2012 – dl.acm.org … 2006; Fujii et al. 2008; Mrozinski et al. 2005; Kawahara et al. 2001; Zhu and Penn 2005; Zhang et al. 2007a]. A large amount of document and reference summary pairs are needed when train- ing automatic extractive summarization systems with high accuracy. The reference … Cited by 2 Related articles

Assessing sentence scoring techniques for extractive text summarization R Ferreira, L de Souza Cabral, RD Lins… – Expert systems with …, 2013 – Elsevier … sentences. In terms of extractive summarization, sentence scoring is the technique most used for extractive text summarization. … suggested. Keywords. Extractive summarization; Sentence scoring methods; Summarization evaluation. 1. Introduction. … Cited by 5 Related articles All 3 versions

Automatic extractive text summarization based on fuzzy logic: a sentence oriented approach ME Hannah, TV Geetha, S Mukherjee – Swarm, Evolutionary, and Memetic …, 2011 – Springer … The Precision, Recall and F-score values of the compressed text are generated using ROUGE-1, which is claimed to suit extractive summarization systems better. We have the results of sen- tence oriented summarizer that uses fuzzy approach and the results are promising. … Cited by 3 Related articles All 3 versions

Evaluation Approaches for an Arabic Extractive Generic Text Summarization System I Sobh, N Darwish, M Fayek – … of 2nd International Conference on Arabic …, 2009 – rdi-eg.com … Size of produced summary can be very short (Headline) or relatively short typically 20% to 25% of original document size. Extractive Summarization Extractive summarization extracts text by selecting from original document important pieces to produce shorter result. … Cited by 1 Related articles All 3 versions

Extractive email thread summarization: Can we do better than He Said She Said? PA Duboue – Proceedings of the Seventh International Natural …, 2012 – dl.acm.org … Natu- ral Language Engineering, 10(3-4):327–348. Kathleen McKeown, Lokesh Shrestha, and Owen Ram- bow. 2007. Using question-answer pairs in extractive summarization of email conversations. In CICLing, volume 4394 of LNCS, pages 542–550. Springer. GA Miller. … Cited by 1 Related articles All 10 versions

Corpus Based Extractive Document Summarization for Indic Script PV Reddy, BV Vardhan… – … Processing (IALP), 2011 …, 2011 – ieeexplore.ieee.org … Document summarization approaches are broadly classified into to ie extractive summarization approach and abstractive summarization approach. In this paper, e performed single document summarization to generate summary … All 4 versions

Improving coherence by reordering the output of extractive summarization using Centering Theory through genetic algorithm R Manurung – Advanced Computer Science and Information …, 2013 – ieeexplore.ieee.org Abstract—Extractive summarization is a widely studied and fairly easy to implement technique. It works by choosing the most important parts of a document (s) as a summary. However, this can lead to a lack of coherence in the summary itself. In this study, the … Related articles

Survey on Extractive Text Summarization Approaches MS Patil, MS Bewoor, SH Patil – nci2tm.sinhgad.edu … summarization. Two main approaches focused are clustering techniques and machine learning technique (SVM). Keywords— abstractive summarization, clustering, extractive summarization, pre-processing, SVM I. INTRODUCTION … Related articles

On the effect of stemming algorithms on extractive summarization: a case study E Galiotou, N Karanikolas, C Tsoulloftas – Proceedings of the 17th …, 2013 – dl.acm.org Abstract In this paper, we discuss the efficiency of stemming algorithms and their contribution to the improvement of shallow summarization methods. We describe a benchmarking experiment on the use of two stemming algorithms and two different sets of … Related articles

Topic-Level Extractive Summarization of Lectures and Meetings Using a Snippet Similarity Graph CA Bhatt, A Popescu-Belis – 2014 – infoscience.epfl.ch Abstract In this paper, we present an approach for topic-level video snippet-based extractive summarization, which relies on con tent-based recommendation techniques. We identify topic-level snippets using transcripts of all videos in the dataset and indexed these …

Extractive Summarization Of Farsi Documents Based On PSO Clustering M Bazghandi, GT Tabrizi, MV Jahan, I Mashahd – jiA, 2012 – vafaeijahan.com Abstract As there is an ever-increasing number of textual resources, users nowadays enjoy access to a wider range of data; hence, accessing accurate and reliable ones has become a problematic issue. Automated summarization systems can play a principal role in covering … Related articles All 5 versions

Extractive Summarization using Continuous Vector Space Models M Kågebäck, O Mogren, N Tahmasebi… – Proceedings of the 2nd …, 2014 – aclweb.org Abstract Automatic summarization can help users extract the most important pieces of information from the vast amount of text digitized into electronic form everyday. Central to automatic summarization is the notion of similarity between sentences in text. In this paper … Related articles All 2 versions

Improving readability through extractive summarization for learners with reading difficulties K Nandhini, SR Balasundaram – Egyptian Informatics Journal, 2013 – Elsevier Abstract In this paper, we describe the design and evaluation of extractive summarization approach to assist the learners with reading difficulties. As existing summarization approaches inherently assign more weights to the important sentences, our approach … Related articles

Polytope Model for Extractive Summarization. M Litvak, N Vanetik – KDIR, 2012 – cs.bgu.ac.il Abstract: The problem of text summarization for a collection of documents is defined as the problem of selecting a small subset of sentences so that the contents and meaning of the original document set are preserved in the best possible way. In this paper we present a … Related articles

Graph Ranking on Maximal Frequent Sequences for Single Extractive Text Summarization Y Ledeneva, RA García-Hernández… – … Linguistics and Intelligent …, 2014 – Springer … An extractive summarization method only decides, for each sentence, whether it should be included in the summary. The resulting summary reads rather awkward; however, simplicity of the underlying statistical techniques makes … Related articles All 5 versions

Investigating The Extractive Summarization Of Literary Novels R Mihalcea – 2011 – digital.library.unt.edu 1.1. Motivation and Problem Definition Due to the vast amount of information we are faced with, summarization has become a critical necessity of everyday human life. When we apply for a job, we first prepare a resume, which summarizes all of our achievements to date to a … Related articles

Extractive Summarization Method for Contact Center Dialogues based on Call Logs. A Tamura, K Ishikawa, M Saikou, M Tsuchida – IJCNLP, 2011 – aclweb.org Abstract This paper proposes a novel extractive summarization method for speech dialogues between agents and customers in contact centers. The proposed method does not require any extra cost for applying the method such as preparing rules or creating … Related articles All 3 versions

[BOOK] Extractive speech summarization using structural modeling J Zhang, P Adviser-Fung – 2011 – dl.acm.org … top of page ABSTRACT. In this dissertation, we propose a new rhetorical structure modeling approach as a critical step in the understanding of extractive summarization of spoken documents. Previous work has shown that explicit … All 2 versions

Shallow Semantics for Extractive Summarization using Connexor Machinese Semantics D Kipp – on Automatic Text Summarization 2011, 2011 – cs.toronto.edu Abstract. Connexor Machinese Semantics is one of the most elaborate tools for providing semantic information about a sentence. It has been hypothesized that semantic analysis of sentences is required in order to make significant improvements in automatic … Related articles All 2 versions

A Survey on Existing Extractive Text Summarization Techniques N Arackal, PM Dhanya – 2014 – csidl.org … Text summarization gives support to other tasks such as text classification [2]. Summarization can be broadly divided into two categories namely extractive summarization and abstractive summarization [2]. In extractive summarization [3], the goal is to identifying most important … Related articles

Extractive Summarization and Dialogue Act Modeling on Email Threads: An Integrated Probabilistic Approach T Oya, G Carenini – cs.ubc.ca Abstract In this paper, we present a novel supervised approach to the problem of summarizing email conversations and modeling dialogue acts. We assume that there is a relationship between dialogue acts and important sentences. Based on this assumption, … Related articles All 2 versions

Empirical analysis of exploiting review helpfulness for extractive summarization of online reviews W Xiong, D Litman – people.cs.pitt.edu Abstract We propose a novel unsupervised extractive approach for summarizing online reviews by exploiting review helpfulness ratings. In addition to using the helpfulness ratings for review-level filtering, we suggest using them as the supervision of a topic model for …

Complete Pre Processing Phase of Punjabi Text Extractive Summarization System. V Gupta, GS Lehal – COLING (Demos), 2012 – kde.cs.tut.ac.jp ABSTRACT Text Summarization is condensing the source text into shorter form and retaining its information content and overall meaning. Punjabi text Summarization system is text extraction based summarization system which is used to summarize the Punjabi text … Related articles All 8 versions

A Study of Automatic Text Summarization using Extractive Techniques SCA Jaya – ijrate.org … Extractive summarization methods try to find out the most important topics of an input document and select sentences that are related to these chosen concepts to create the summary. This paper presents an overview of four … Related articles

Exploring Domain-Sensitive Features for Extractive Summarization in the Medical Domain DT Nguyen, J Leveling – Natural Language Processing and Information …, 2013 – Springer Abstract This paper describes experiments to adapt document summarization to the medical domain. Our summarizer combines linguistic features corresponding to text fragments (typically sentences) and applies a machine learning approach to extract the most … Cited by 1 Related articles All 3 versions

Overview of Text Summarization Extractive Techniques MP AN – ijecs.in … An extractive summarization method consists of selecting important Sentences, paragraphs etc. … We explore different types of summarization, evaluation strategies and metrics, features, extractive summarization techniques, approaches and problems in text summarization. … Related articles

A learning-based sampling approach to extractive summarization V Juneja, S Germesin, T Kleinbauer – … of the NAACL HLT 2010 Student …, 2010 – dl.acm.org Abstract In this paper we present a novel resampling model for extractive meeting summarization. With resampling based on the output of a baseline classifier, our method outperforms previous research in the field. Further, we compare an existing resampling … Related articles All 8 versions

A Hybrid Approach for Extractive Document Summarization Using Machine Learning and Clustering Technique MS Patil, MS Bewoor, SH Patil – ijcsit.com … Broadly, text summarization can be classified into two types: Extractive: Extractive summarization methods simplify the problem of summarization into the problem of selecting a representative subset of the sentences in the original documents. … Related articles All 2 versions

A Recurrent Neural Network Language Modeling Framework For Extractive Speech Summarization KY Chen, SH Liu, B Chen, HM Wang, WL Hsu… – iis.sinica.edu.tw … summarization. More specifically, ILP method reformulates the extractive summarization task as an optimization problem with a set of constrains, and then selects an optimal sentence combination by using integer linear programming. …

Single document extractive text summarization using Genetic Algorithms N Chatterjee, A Mittal, S Goyal – Emerging Applications of …, 2012 – ieeexplore.ieee.org … In extractive summarization, the summarizer works towards identifying the most important sentences of the said document, as opposed to abstractive summarization which creates a gist of a document by capturing the underlying semantics [7]. The number of sentences to be … Related articles

Improved MMR Technique for Extractive Text Summarization M Kiabod, MN Dehkordi, SM Sharafi – aeuso.org … 4985–4988. [21] G. Murray, S. Renals and J. Carletta, “Extractive summarization of meeting Recordings”, in Proceedings of 9th European Conference on Speech Communication and Technology, 2005; 593–596. [22] R. McDonald … Related articles

Proposing an Extractive Mono-Document Summarization System for Persian Language S Masoumi, R Tabatabaei… – Journal of …, 2013 – ingentaconnect.com … Keywords: Summarization, Text Summarizer, Mono-Document Summarization, Extractive Summarization, Persian Text Summarization. … An extractive summarization method consists of selecting important sentences, para- graphs etc. …

Effect of Near-orthogonality on Random Indexing Based Extractive Text Summarization N Chatterjee, PK Sahoo – International Journal of Innovation and …, 2013 – issr-journals.org … A study of near-orthogonality is therefore considered primary before advocating RI as a viable alternative to other WSM based approaches for extractive summarization. … In section 3 Random Indexing and RISUM approach for extractive summarization has been presented. … Related articles All 3 versions

Extractive text summarization: can we use the same techniques for any text? T Vodolazova, E Lloret, R Muñoz… – … Language Processing and …, 2013 – Springer … The extractive summarization systems developed so far have been tested on a number of different corpora [22]. … 2 Related Work With the evolution of technology different methods and heuristics have been used to improve extractive summarization systems. … Related articles All 4 versions

A Survey of Extractive and Abstractive Text Summarization Techniques V Dalal, L Malik – Emerging Trends in Engineering and …, 2013 – ieeexplore.ieee.org … methods. II. SURVEY OF EXTRACTIVE SUMMARIZATION The extractive automatic text summarization wor) involving bioYinspired algorithms is as follows. MS Binwahlan et al [1] introduced a wor) for feature selection. They … Related articles

The Extractive Text Summarization Technique: A Review Paper A Verma – cbsmohali.org … There study reviewed the advantage and disadvantage of the using the said technique. Findings: Although there are few problems, which exist with extractive summarization, still it is the most widely used technique and is effective too. … Related articles

Extractive single-document summarization based on genetic operators and guided local search M Mendoza, S Bonilla, C Noguera, C Cobos… – Expert Systems with …, 2014 – Elsevier … Evolutionary algorithms have traditionally shown good results in solving the problem of extractive summarization (Aliguliyev, 2009a, Binwahlan et al., 2009, Binwahlan et al., 2010, Fattah and Ren, 2009, Litvak et al., 2010, Qazvinian et al., 2008, Shareghi and Hassanabadi … Related articles All 4 versions