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2016 | OriginalPaper | Chapter

Extractive Text Summarization Using Lexical Association and Graph Based Text Analysis

Authors : R. V. V. Murali Krishna, Ch. Satyananda Reddy

Published in: Computational Intelligence in Data Mining—Volume 1

Publisher: Springer India

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Abstract

Keyword extraction is an important phase in automatic text summarization process because it directly affects the relevance of the system generated summary. There are many procedures for extracting keywords, but all of these aim to find the words that directly represent the topic of the document. Identifying lexical association between terms is one of the existing techniques proposed for determining the topic of the document. In this paper, we have made use of lexical association and graph based ranking techniques for retrieving keywords from a source text and subsequently to assign them a relative weight. The individual weights of the extracted keywords are used to rank the sentences in the source text. Our summarization system is tested with DUC 2002 dataset and is found to be effective when compared to the existing context based summarization systems.

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Literature
1.
Hovy, E.H., Lin, C.Y.: Automated text summarization in SUMMARIST, pp. 81–94. MIT Press (1999)
2.
Gholamrezazadeh, S., Salehi, M.A., Gholamzadeh, B.: A comprehensive survey on text summarization systems. In: 2nd International Conference on Computer Science and Its Applications, pp. 1, 6, 10–12. (2009)
3.
Kamble, P., Dharmadhikari, S.C.: Context based topical document summarization. Data Mining Knowl. Eng. 6, 146–150 (2014)
4.
Pawar, D.D., Bewoor, M.S., Patil, S.H.: Context based indexing in text summarization using lexical association. Int. J. Eng. Res. Technol. 2(12), (2013)
5.
Ferreira, R., Freitas, F., de Souza Cabral, L., Lins, R.D., Lima, R., França, G., Simske, S.J., Favaro, L.: A context based text summarization system. In: Document Analysis Systems (DAS), 11th IAPR International Workshop, pp. 66–70. (2014)
6.
Goyal, P., Behera, L., McGinnity, T.M.: A context-based word indexing model for document summarization. IEEE Trans. Knowl. Data Eng. 25(8), 1693–1705 (2013)
7.
Matsuo, Y., Ishizuka, M.: Keyword extraction from a single document using word co-occurrence statistical information. In: FLAIRS Conference, AAAI Press, pp. 392–396. (2003)
8.
Lott, B.: Survey of Keyword Extraction Techniques. UNM Education (2012)
9.
Wartena, C., Brussee, R., Slakhorst, W.: Keyword extraction using word co-occurrence. In: Workshop on Database and Expert Systems Applications (DEXA), IEEE, pp. 54–58. (2010)
10.
Rajaraman, A., Ullman, J.D.: Data Mining. Mining of Massive Datasets, pp. 1–17. (2011)
11.
Wan, X., Xiao, J.: Exploiting neighborhood knowledge for single document summarization and keyphrase extraction. ACM Trans. Inf. Syst. 28, 8:1–8:34 (2010)
12.
Mihalcea, R., Tarau, P.: Textrank: bringing order into texts. In Lin, D., Wu, D. (eds.), Proceedings of EMNLP, pp. 404 (2004)
13.
Brin, S., Page, L.: The anatomy of a large-scale hypertextual Web search engine. Comput. Netw. ISDN Syst. 30, 1–7 (1998)CrossRef
14.
Aggarwal, C.C., Zhao, P.: Towards graphical models for text processing. Knowl. Inf. Syst. 36(1), 1–21 (2013)CrossRef
15.
Toutanova, K., Klein, D., Manning, C., Singer, Y.: Feature-rich part-of-speech tagging with a cyclic dependency network. In: Proceedings of HLTNAACL, pp. 252–259. (2003)
16.
Toutanova, K., Manning, C.D.: Enriching the knowledge sources used in a maximum entropy part-of-speech tagger. In: Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-2000), pp. 63–70. (2000)
17.
Over, P., Liggett, W.: Introduction to DUC: an intrinsic evaluation of generic news text summarization systems. In: Proceedings of DUC workshop Text Summarization. (2002)
18.
Lin, C.Y., Hovy, E.H.: Automatic evaluation of summaries using N-gram co-occurrence statistics. In: Proceedings of 2003 Language Technology Conference (HLT-NAACL), pp. 71–78. (2003)
Metadata
Title
Extractive Text Summarization Using Lexical Association and Graph Based Text Analysis
Authors
R. V. V. Murali Krishna
Ch. Satyananda Reddy
Copyright Year
2016
Publisher
Springer India
Book
Computational Intelligence in Data Mining—Volume 1

Print ISBN: 978-81-322-2732-8

Electronic ISBN: 978-81-322-2734-2

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-81-322-2734-2_27

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