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

6 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. To demonstrate the applicability of the proposed summarization procedure, we used Martin Luther King, Jr’s public speech

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages285-292
Number of pages8
Volume9101
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)03029743
ISSN (Electronic)16113349

Other

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

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Keywords

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

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Cho, S. G., & Kim, S. B. (2015). Summarization of documents by finding key sentences based on social network analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9101, pp. 285-292). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9101). Springer Verlag. https://doi.org/10.1007/978-3-319-19066-2_28