Update Summarization Based on Latent Semantic Analysis

Update Summarization Based on Latent Semantic Analysis

This paper deals with our recent research in text summarization.We went from single-document summarization through multidocumentsummarization to update summarization. We describe the developmentof our summarizer which is based on latent semantic analysis(LSA) and propose the update summarization component which determinesthe redundancy and novelty of each topic discovered by LSA. Thefinal part of this paper presents the results of our participation in theexperiment of Text Analysis Conference 2008.

Keywords: Multi-Document Summarization, Update Summarization, Summarization Evaluation, Text Analysis Conference

Year: 2009

Journal ISSN: 0302-9743
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Authors of this publication:

Josef Steinberger

E-mail: jstein@kiv.zcu.cz

Josef is an associated professor at the Department of computer science and engineering at the University of West Bohemia in Pilsen, Czech Republic. He is interested in media monitoring and analysis, mainly automatic text summarisation, sentiment analysis and coreference resolution.

Karel Je┼żek

Phone:  +420 377632475, 377632400
E-mail: jezek_ka@kiv.zcu.cz
WWW: http://www-kiv.zcu.cz/~jezek_ka/

Karel is a group coordinator and a supervisor of PhD students working at research projects of this Group.

Related Projects:


Automatic Text Summarisation

Authors:  Josef Steinberger, Karel Je┼żek, Michal Campr, Ji┼Ö├ş Hynek
Desc.:Automatic text summarisation using various text mining methods, mainly Latent Semantic Analysis (LSA).