Summarization of documents by finding key sentences based on social network analysis

Su Gon Cho, Seoung Bum Kim

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    7 Citations (Scopus)

    Abstract

    Finding key sentences or paragraphs from a document is an important and challenging problem. In recent years, the amount of text data has grown astronomically and this growth has produced a great demand for text summarization. In the present study, we propose a new text summarization process by text mining and social network methods.

    Original languageEnglish
    Title of host publicationCurrent Approaches in Applied Artificial Intelligence - 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015, Proceedings
    EditorsChang-Hwan Lee, Yongdai Kim, Young Sig Kwon, Juntae Kim, Moonis Ali
    PublisherSpringer Verlag
    Pages285-292
    Number of pages8
    ISBN (Print)9783319190655
    DOIs
    Publication statusPublished - 2015
    Event28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015 - Seoul, Korea, Republic of
    Duration: 2015 Jun 102015 Jun 12

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume9101
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015
    Country/TerritoryKorea, Republic of
    CitySeoul
    Period15/6/1015/6/12

    Bibliographical note

    Publisher Copyright:
    © Springer International Publishing Switzerland 2015.

    Keywords

    • Centrality degree
    • Social network
    • Text mining
    • Text summarization

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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