Presentation 2006-07-28
Examination of Select-and-Complement Summarization Model
Satoshi Ikeda, Megumi Makino, Kazuhide Yamamoto,
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Abstract(in English) There has been many works on summarization of the sentence. Most of these them make a summary by extracting words from the original sentence. Therefore, the summary don't have expressions not in the original sentence. In contrast, there are expressions not in the original in manual summarization. Consequently, our aim here is to generate a summary in a natural way that a human does. That is, we propose a summarization method in which we extract terms necessary to make a summary from original sentence, and generate a sentence from those terms. We used SVM for extracting terms necessary to make summarization, and statistical information from general corpus to generate the sentence. The experimental result showed the performance of readability is 36% and meaning identification is 45% under the summary rate of 80%.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) automatic summarization / extract term / generate sentence
Paper # NLC2006-13
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Conference Information
Committee NLC
Conference Date 2006/7/21(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) Examination of Select-and-Complement Summarization Model
Sub Title (in English)
Keyword(1) automatic summarization
Keyword(2) extract term
Keyword(3) generate sentence
1st Author's Name Satoshi Ikeda
1st Author's Affiliation Department of Electrical Engineering, Nagaoka University of Technology()
2nd Author's Name Megumi Makino
2nd Author's Affiliation Department of Electrical Engineering, Nagaoka University of Technology
3rd Author's Name Kazuhide Yamamoto
3rd Author's Affiliation Department of Electrical Engineering, Nagaoka University of Technology
Date 2006-07-28
Paper # NLC2006-13
Volume (vol) vol.106
Number (no) 191
Page pp.pp.-
#Pages 6
Date of Issue