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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