Presentation | 2011-01-27 Text mining system STM based on semantic analysis Minoru HARADA, Ryo ISHIDA, Kazuhiro YAMANISHI, Yoshiki KANDA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Current text mining based on the analysis on surface information of the morpheme and dependency among words cannot understand word meaning and functional relations between words, so it cannot find the knowledge concerning the relation that consists of two or more words such as "What is what" and "What does what do". Our text mining system STM analyzes sentences and phrases on the basis of the similarity of meaning of their content. In STM, Japanese sentences are converted into semantic graphs by our semantic analysis system Sage, and the degree of similarity of two sentences is measured based on the size of the similar common subgraph that consists of node pairs having similar meaning and arc pairs united by similar deep cases. As a result, the sentences with a similar meaning even if their expression are different are classified in a similar opinion cluster. In addition, the classification based on opinion person's feelings can be done by using the feelings word dictionary, the idiom dictionary, and the emoticon dictionary originally collected. Thus, we explain how a past text mining can be upgraded based on the semantic analysis. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Semantic analysis / Text mining / Feeling analysis Reputation analysis / Causality analysis / Sentence similarity |
Paper # | NLC2010-35 |
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Committee | NLC |
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Conference Date | 2011/1/20(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Natural Language Understanding and Models of Communication (NLC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Text mining system STM based on semantic analysis |
Sub Title (in English) | |
Keyword(1) | Semantic analysis |
Keyword(2) | Text mining |
Keyword(3) | Feeling analysis Reputation analysis |
Keyword(4) | Causality analysis |
Keyword(5) | Sentence similarity |
1st Author's Name | Minoru HARADA |
1st Author's Affiliation | Faculty of Science and Engineering, Department of Integrated Information Technology, Aoyama Gakuin University() |
2nd Author's Name | Ryo ISHIDA |
2nd Author's Affiliation | Graduate School of Science and Engineering, Aoyama Gakuin University |
3rd Author's Name | Kazuhiro YAMANISHI |
3rd Author's Affiliation | Graduate School of Science and Engineering, Aoyama Gakuin University |
4th Author's Name | Yoshiki KANDA |
4th Author's Affiliation | Undergraduate School of Science and Engineering, Aoyama Gakuin University |
Date | 2011-01-27 |
Paper # | NLC2010-35 |
Volume (vol) | vol.110 |
Number (no) | 400 |
Page | pp.pp.- |
#Pages | 6 |
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