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Extractive Text Summarization Using Lexical Association and Graph Based Text Analysis

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Computational Intelligence in Data Mining—Volume 1

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 410))

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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Authors and Affiliations

  1. IT Department, G.V.P College of Engineering (A), Visakhapatnam, India

    R. V. V. Murali Krishna

  2. CS & SE Department, Andhra University, Visakhapatnam, India

    Ch. Satyananda Reddy

Authors
  1. R. V. V. Murali Krishna
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  2. Ch. Satyananda Reddy
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Corresponding author

Correspondence to R. V. V. Murali Krishna .

Editor information

Editors and Affiliations

  1. Veer Surendra Sai University of Tech., Dept of Computer Sci Eng & IT, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  2. National Institute of Technology, Dept. of Computer Science & Engineering, Rourkela, Odisha, India

    Durga Prasad Mohapatra

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Murali Krishna, R.V.V., Satyananda Reddy, C. (2016). Extractive Text Summarization Using Lexical Association and Graph Based Text Analysis. In: Behera, H., Mohapatra, D. (eds) Computational Intelligence in Data Mining—Volume 1. Advances in Intelligent Systems and Computing, vol 410. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2734-2_27

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

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2732-8

  • Online ISBN: 978-81-322-2734-2

  • eBook Packages: EngineeringEngineering (R0)

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