Fuzzy-rough set aided sentence extraction summarization

Hsun Hui Huang, Yau Hwang Kuo, Horng Chang Yang

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

23 Citations (Scopus)

Abstract

In this paper, a novel method is proposed to extract key sentences of a document as its summary by estimating the relevance of sentences through the use of fuzzy-rough sets. This method uses senses rather than raw words to lessen the problem that sentences of the same or similar semantic meaning but written in synonyms are treated differently. Also included is semantic clustering, used to avoid selecting redundant key sentences. A prototype of this automatic text summarization scheme is constructed and an intrinsic method with criteria widely used in informationretrieval systems is employed for measuring the summary quality. The results of applying the prototype to datasets with manually-generated summaries are shown.

Original languageEnglish
Title of host publicationFirst International Conference on Innovative Computing, Information and Control 2006, ICICIC'06
Pages450-453
Number of pages4
DOIs
Publication statusPublished - 2006
Event1st International Conference on Innovative Computing, Information and Control 2006, ICICIC'06 - Beijing, United States
Duration: 2006 Aug 302006 Sept 1

Publication series

NameFirst International Conference on Innovative Computing, Information and Control 2006, ICICIC'06

Other

Other1st International Conference on Innovative Computing, Information and Control 2006, ICICIC'06
Country/TerritoryUnited States
CityBeijing
Period06-08-3006-09-01

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Mechanical Engineering

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