Presentation 1996/7/18
Relevant Newspaper Articles Summarization by Redundancy Reduction
Takahiro Funasaka, Kazuhide Yamamoto, Shigeru Masuyama,
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Abstract(in English) In recent years, we can retrieve newspaper articles easily, because they are provided in machine readable forms. However, if we retrieve articles on long term cases and political issues, many articles are retrieved and it takes much time to read them. Thus developing relevant articles summarization method is very useful. In this study, we propose a method of summarizing relevant newspaper articles by eliminating redundancy parts and guess sentences based on the observations that fact sentences are more important than guess sentences and that relevant articles have redundant parts.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) summarization / newspaper articles / redundancy reduction
Paper # NLC96-15
Date of Issue

Conference Information
Committee NLC
Conference Date 1996/7/18(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Relevant Newspaper Articles Summarization by Redundancy Reduction
Sub Title (in English)
Keyword(1) summarization
Keyword(2) newspaper articles
Keyword(3) redundancy reduction
1st Author's Name Takahiro Funasaka
1st Author's Affiliation Department of Knowledge-based Information Engineering, Toyohashi University of Technology()
2nd Author's Name Kazuhide Yamamoto
2nd Author's Affiliation ATR Interpreting Telecommunication Laboratories
3rd Author's Name Shigeru Masuyama
3rd Author's Affiliation Department of Knowledge-based Information Engineering, Toyohashi University of Technology
Date 1996/7/18
Paper # NLC96-15
Volume (vol) vol.96
Number (no) 157
Page pp.pp.-
#Pages 8
Date of Issue