Presentation 2011-01-21
Novel Social-graph Representation to Extract Hidden Common Relations between People
Kazufumi YOGO, Ryoichi SHINKUMA, Hiroyuki KASAI, Kazuhiro YAMAGUCHI, Tatsuro TAKAHASHI,
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Abstract(in English) Predicting potential demands of people, which the people have not recognized or can not express precisely by themselves, can be useful for services which provide content pieces for users. Social graphs, which represent relationship between people, are used for predicting people demand in the current internet-based services. However, these graphs cannot represent such relationships that two users reside in common communities or common places. In this paper, therefore, we propose to represent not only a person but also other things including a community and a social event, together as a node in a social graph. Our representation allows us to estimate who share a potential interest with a given person. We validate our representation using a real relational dataset.
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Keyword(in English) Social Graph / Demand Prediction / Potential Relation / Link Estimation
Paper # NS2010-156
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Committee NS
Conference Date 2011/1/13(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Novel Social-graph Representation to Extract Hidden Common Relations between People
Sub Title (in English)
Keyword(1) Social Graph
Keyword(2) Demand Prediction
Keyword(3) Potential Relation
Keyword(4) Link Estimation
1st Author's Name Kazufumi YOGO
1st Author's Affiliation Graduate School of Informatics, Kyoto University()
2nd Author's Name Ryoichi SHINKUMA
2nd Author's Affiliation Graduate School of Informatics, Kyoto University
3rd Author's Name Hiroyuki KASAI
3rd Author's Affiliation Graduate School of Information Systems, the University of Electro-Communications
4th Author's Name Kazuhiro YAMAGUCHI
4th Author's Affiliation Kobe Digital Labo
5th Author's Name Tatsuro TAKAHASHI
5th Author's Affiliation Graduate School of Informatics, Kyoto University
Date 2011-01-21
Paper # NS2010-156
Volume (vol) vol.110
Number (no) 372
Page pp.pp.-
#Pages 4
Date of Issue