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Achieving More Coherent Summaries in Automatic Text Summarization; an Ontology-based Approach

Majid Ramezani, Mohammad-Reza Feizi-Derakhshi
2016 British Journal of Mathematics & Computer Science  
One of the main requirements of the machine produced texts, is their coherence and the semantic relation between their sentences.  ...  The main purpose of this paper is how to achieve more coherent summaries in automatic text summarization process.  ...  Also based on their output, text summarization systems are categorized as 'generic' or 'query-based'.  ... 
doi:10.9734/bjmcs/2016/27549 fatcat:hbehc4u5kjgvzlaslnouu2qa4y

Text Summarization using Centrality Concept

Ghaleb Algaphari, Fadl M. Ba-Alwi, Aimen Moharram
2013 International Journal of Computer Applications  
This paper investigates a graph based centrality algorithm on Arabic text summarization problem (ATS).  ...  The algorithm starts computing the similarity between two sentences and evaluating the centrality of each sentence in a cluster based on centrality graph.  ...  The manual assessment was based on the text overall responsiveness and the automatic assessment used ROUGE method.  ... 
doi:10.5120/13703-1450 fatcat:5wrvp3bbd5a75ebfh4jf6vdnv4

Extractive summarization using complex networks and syntactic dependency

Diego R. Amancio, Maria G.V. Nunes, Osvaldo N. Oliveira, Luciano da F. Costa
2012 Physica A: Statistical Mechanics and its Applications  
Using strategies based on diversity metrics, a better performance in automatic summarization is achieved in comparison to previous work employing complex networks.  ...  These results reinforce the suitability of complex network methods for improving automatic summarizers in particular, and treating text in general.  ...  In this paper, the metrics used are precision, recall and F -measure available on the package for automatic evaluation ROUGE [42] , based on the co-occurrence of units (n-grams) between automatically  ... 
doi:10.1016/j.physa.2011.10.015 fatcat:g4m2uphhonfxhmnhr5mbv6tpn4

Towards Robust Abstractive Multi-Document Summarization: A Caseframe Analysis of Centrality and Domain

Jackie Chi Kit Cheung, Gerald Penn
2013 Annual Meeting of the Association for Computational Linguistics  
In automatic summarization, centrality is the notion that a summary should contain the core parts of the source text.  ...  These results suggest that substantial improvements are unlikely to result from better optimizing centrality-based criteria, but rather more domain knowledge is needed.  ...  Introduction In automatic summarization, centrality has been one of the guiding principles for content selection in extractive systems.  ... 
dblp:conf/acl/CheungP13a fatcat:hlu63fsbk5fr5ine4ep3e3va4a

A Survey to Text Summarization Methods for Turkish

Çağdaş Can, Özgün Koşaner, Özlem Aktaş
2016 International Journal of Computer Applications  
Brief summary of the methods used for automatic text summarization in the literature, and also brief definitions of summary, abstraction and automatic text summarization are given.  ...  Nowadays, people deal with a huge amount of data, especially while they are surfing on internet. So, this makes the topic of automatic summarization is very important and in the forefront.  ...  Erkan & Radev presented a new approach to define sentence salience based on graphbased centrality scoring of sentences.  ... 
doi:10.5120/ijca2016910358 fatcat:ksezeyftsjgcrosoclshdugqge

Automatic Summarization of Polish News Articles by Sentence Selection

Krzysztof Jassem, Łukasz Pawluczuk
2015 Proceedings of the 2015 Federated Conference on Computer Science and Information Systems  
This paper describes the automatic summarization system developed for the Polish language.  ...  The system implements sentence-based extractive summarization technique, which consists in determining most important sentences in document due to their computed salience.  ...  REVIEW OF EXPERIMENTS ON SUMMARIZATION OF POLISH TEXTS This section covers experiments on automatic summarization for the Polish language, resulting in theoretical works, as well as working implementations  ... 
doi:10.15439/2015f186 dblp:conf/fedcsis/JassemP15 fatcat:43zicuuvuvgipkxybpu7t5vpjq

Extractive Text Summarization System using Fuzzy Clustering Algorithm

P. Vishnu Raja, K. Sangeetha, D. Deepa
2016 Asian Journal of Research in Social Sciences and Humanities  
The automatic document summarization is used to solve the problem of information overload.  ...  Experimental results on quotation dataset show that the algorithm performs far better as compare to the K-medoids algorithm.  ...  Generally extractive summarization technique based on sentences is used for automatic text summarization.  ... 
doi:10.5958/2249-7315.2016.00407.x fatcat:2e3s7c2lgnhsplwco23i3b5c4e

Modeling, comprehending and summarizing textual content by graphs [article]

Vinicius Woloszyn, Guilherme Medeiros Machado, Leandro Krug Wives, José Palazzo Moreira de Oliveira
2018 arXiv   pre-print
One manner to summarize texts consists of using a graph model.  ...  Automatic Text Summarization strategies have been successfully employed to digest text collections and extract its essential content.  ...  ROUGE was chosen because it is one of most used measures in the fields of Machine Translation and Automatic Text Summarization [19] .  ... 
arXiv:1807.00303v1 fatcat:ldrs2fpdnnbopjtkktyixjybyi

Review on automatic text summarization

Abirami Rajasekaran, Dr R. Varalakshmi
2018 International Journal of Engineering & Technology  
Past few years have witnessed a rapid growth in the research of summarizing the text automatically using different approaches.  ...  This paper provides an in-depth review of the vari-ous approaches, techniques, methods involved in Automatic Text Summarization.  ...  The connection between the sentences are associated based on the similarity relation.  ... 
doi:10.14419/ijet.v7i2.33.14210 fatcat:z7lffdxnwnejlgcytgs24va4mq

Evolutionary Algorithm for Extractive Text Summarization

Rasim ALGULIEV, Ramiz ALIGULIYEV
2009 Intelligent Information Management  
Text summarization is the process of automatically creating a compressed version of a given document preserving its information content.  ...  Abstractive summarization may compose novel sentences, unseen in the original sources. In our study we focus on sentence based extractive document summarization.  ...  Ren, "GA, MR, FFNN, PNN and GMM based models for automatic text summarization," Computer Speech and Language, Vol. 23, No. 1, pp.  ... 
doi:10.4236/iim.2009.12019 fatcat:kb3aonicljgrxdlhb3aso463ou

Addressing the Problem of Coherence in Automatic Text Summarization: A Latent Semantic Analysis Approach

Abdulfattah Omar
2017 International Journal of English Linguistics  
This study, therefore, tends to bridge the gap between literature and summarization theory by proposing a summarization system that is based on more semantic-based approaches for extracting more meaningful  ...  This article is concerned with addressing the problem of coherence in the automatic summarization of prose fiction texts.  ...  The extracted sentences are central to the development of the action. There is a high degree of agreement between the manual summaries on the one hand and the automatic ones on the other.  ... 
doi:10.5539/ijel.v7n4p33 fatcat:3zrbkh4oujhopgqdwks6pamjam

Automatic Summarization of Textual Document

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
To find out the relevant information from this large amount of data, we need an automatic mechanism that will extract the useful data. Such automatic systems are automatic summarization systems.  ...  method to interpret and examine the text.  ...  Weights of the features will depend on the context of the document and they change when text data changes. If a dataset is changed their features weights will change automatically.  ... 
doi:10.35940/ijitee.a4400.119119 fatcat:fpgb2k7fyzgbfeg5hju6e5iopm

LexRank: Graph-based Lexical Centrality as Salience in Text Summarization

G. Erkan, D. R. Radev
2004 The Journal of Artificial Intelligence Research  
We introduce a stochastic graph-based method for computing relative importance of textual units for Natural Language Processing. We test the technique on the problem of Text Summarization (TS).  ...  We consider a new approach, LexRank, for computing sentence importance based on the concept of eigenvector centrality in a graph representation of sentences.  ...  458 LexRank: Graph-based Lexical Centrality as Salience in Text Summarization In Section 2, we present centroid-based summarization, a well-known method for judging sentence centrality.  ... 
doi:10.1613/jair.1523 fatcat:6f5nol2haba7zcphoxjz2qslwe

A New Text Summarization Approach based on Relative Entropy and Document Decomposition

Nawaf Alharbe, Mohamed Ali Rakrouki, Abeer Aljohani, Mashael Khayyat
2022 International Journal of Advanced Computer Science and Applications  
This automatic text summarization is document decomposition according to relative entropy analysis; which means measuring the difference of the probability distribution to measure the correlation between  ...  In fact, text summarization technology is a vital part of text processing, therefore. The focus is on the semantic information not just on the basic information.  ...  In this context, this paper proposes a new method of automatic text summarization based on relative entropy and document decomposition.  ... 
doi:10.14569/ijacsa.2022.0130372 fatcat:grsgvweb4jf5xoaw52rszxijwi

A Study on Ontology Based Abstractive Summarization

M. Jishma Mohan, C. Sunitha, Amal Ganesh, A. Jaya
2016 Procedia Computer Science  
With widespread use of Internet and the emergence of information aggregation on a large scale, a quality text summarization is essential to effectively condense the information.  ...  Automatic summarization systems condense the documents by extracting the most relevant facts. Summarization is commonly classified into two types, extractive and abstractive.  ...  When this is done by means of a computer, i.e. automatically, we call this Automatic Text Summarization [1] .  ... 
doi:10.1016/j.procs.2016.05.122 fatcat:e4d6t3x5bbalbjyhv77vbojtoq
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