A method of collecting know-how knowledge based on question-answer examples and search engine suggests
Authors: 
Jiaqi Li, Chen Zhao, Youchao Lin, Mizuho Baba, Tian Nie, Takehito Utsuro, Yasuhide Kawada, Noriko KandoAuthors Info & Claims
Jiaqi Li, Chen Zhao, Youchao Lin, Mizuho Baba, Tian Nie, Takehito Utsuro, Yasuhide Kawada, Noriko KandoAuthors Info & ClaimsArticle No.: 43, Pages 1 - 8
Abstract
This paper presents techniques of retrieving useful information from a mixture of Web pages collected from either question-answer sites (Q&A sites) or Web search engines. The proposed techniques are designed to discover the maximum possible amount of know-how knowledge from such collections of Web pages, where know-how knowledge is defined as text contents qualified as information source regarding specific domain of questions. The major intent is to build a framework that selects helpful information to provide answers to various problems of interest, such as useful tips to a question. Techniques in this paper primarily attempt to complement knowledge available on Q&A sites with pages collected from search engines via topic models. In order to argue that pages collected from search engine are truly supplements to know- how knowledge on Q&A sites we verify how much extra useful information the Web search engine is able to provide by manually inspecting Web pages aggregated by the topic model.
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- A method of collecting know-how knowledge based on question-answer examples and search engine suggests
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Published In
January 2017
746 pages
ISBN:9781450348881
DOI:10.1145/3022227
Copyright © 2017 ACM.
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Published: 05 January 2017
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IMCOM '17
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IMCOM '17: The 11th International Conference on Ubiquitous Information Management and Communication
January 5 - 7, 2017
Beppu, Japan
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IMCOM '17 Paper Acceptance Rate 113 of 366 submissions, 31%;
Overall Acceptance Rate 213 of 621 submissions, 34%
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