Automatic text summarization based on relevance feedback with query splitting (poster session)

Authors:
Kyoung-Soo Han;Dae-Ho Baek;Hae-Chang Rim
Affiliations:
Natural Language Processing Lab., Dept. of Computer Science and Engineering, Korea University, Seoul 136-701, Korea;Natural Language Processing Lab., Dept. of Computer Science and Engineering, Korea University, Seoul 136-701, Korea;Natural Language Processing Lab., Dept. of Computer Science and Engineering, Korea University, Seoul 136-701, Korea
Venue:
IRAL '00 Proceedings of the fifth international workshop on on Information retrieval with Asian languages
Year:
2000

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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.