Presentation 2013-11-28
Classifying Questions of Product Accidents in Help desk Questions : Using Semantic Orientations of Words and Judicial Precedents of Product Liability law
Koji WAJIMA, Tomomi OGAWA, Toshihiro FURUKAWA,
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Abstract(in English) This paper proposes the methods which classify the kind of questions relative to product accidents as negative documents. Generally, to classify that, the machine leaning based method is used. However, when the training data is insufficient, the machine leaning based method cannot classify questions. Therefore, we propose a new classifying method. The proposed method can classify the questions under the conditions that the training data is insufficient by using the semantic orientations of words and judicial precedents of product liability law. The computational simulation shows the efficiency of the proposed method.
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Keyword(in English) Help Desk / Semantic Orientations / Customer Relationship Management / Data Mining / Naive Bayes Classifier
Paper # ISEC2013-60,LOIS2013-26
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Conference Date 2013/11/21(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Classifying Questions of Product Accidents in Help desk Questions : Using Semantic Orientations of Words and Judicial Precedents of Product Liability law
Sub Title (in English)
Keyword(1) Help Desk
Keyword(2) Semantic Orientations
Keyword(3) Customer Relationship Management
Keyword(4) Data Mining
Keyword(5) Naive Bayes Classifier
1st Author's Name Koji WAJIMA
1st Author's Affiliation School of Industrial Technology, Advanced Institute of Industrial Technology()
2nd Author's Name Tomomi OGAWA
2nd Author's Affiliation Faculty of Engineering, Tokyo University of Science
3rd Author's Name Toshihiro FURUKAWA
3rd Author's Affiliation Faculty of Engineering, Tokyo University of Science
Date 2013-11-28
Paper # ISEC2013-60,LOIS2013-26
Volume (vol) vol.113
Number (no) 327
Page pp.pp.-
#Pages 6
Date of Issue