Automatic text summarization based on relevance feedback with query splitting

Kyoung Soo Han, Dae Ho Back, Hae-Chang Rim

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

11 Citations (Scopus)

Abstract

This paper describes a method of text summarization using a query expansion technique, Generally, summarization systems using query expansion have the problem that feedback query gets biased during a query expansion process. We can alleviate this problem by expanding the initial query into several split feedback queries. Experimental results show that our query splitting method is superior to other methods using query expansion.

Original languageEnglish
Title of host publicationProceedings of the 5th international Workshop on Information Retrieval with Asian Languages, IRAL 2000
PublisherAssociation for Computing Machinery, Inc
Pages201-202
Number of pages2
ISBN (Electronic)1581133006, 9781581133004
DOIs
Publication statusPublished - 2000 Nov 1
Event5th International Workshop on Information Retrieval with Asian Languages, IRAL 2000 - Hong Kong, China
Duration: 2000 Sep 302000 Oct 1

Other

Other5th International Workshop on Information Retrieval with Asian Languages, IRAL 2000
CountryChina
CityHong Kong
Period00/9/3000/10/1

Keywords

  • Query expansion
  • Query splitting
  • Text summarization

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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  • Cite this

    Han, K. S., Back, D. H., & Rim, H-C. (2000). Automatic text summarization based on relevance feedback with query splitting. In Proceedings of the 5th international Workshop on Information Retrieval with Asian Languages, IRAL 2000 (pp. 201-202). Association for Computing Machinery, Inc. https://doi.org/10.1145/355214.355244