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題名 Exploiting endorsement information and social influence for item recommendation
作者 Li, Cheng-Te;Lin, Shou-De;Shan, Man-Kwan
沈錳坤
貢獻者 資訊科學系
關鍵詞 endorsement network;recommendation;social influence;social network
日期 2011-07
上傳時間 27-Aug-2015 17:34:14 (UTC+8)
摘要 Social networking services possess two features: (1) capturing the social relationships among people, represented by the social network, and (2) allowing users to express their preferences on different kinds of items (e.g. photo, celebrity, pages) through endorsing buttons, represented by a kind of endorsement bipartite graph. In this work, using such information, we propose a novel recommendation method, which leverages the viral marketing in the social network and the wisdom of crowds from endorsement network. Our recommendation consists of two parts. First, given some query terms describing user`s preference, we find a set of targeted influencers who have the maximum activation probability on those nodes related to the query terms in the social network. Second, based on the derived targeted influencers as key experts, we recommend items via the endorsement network. We conduct the experiments on DBLP co-authorship social network with author-reference data as the endorsement network. The results show our method can achieve effective recommendations.
關聯 SIGIR `11 Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval,1131-1132
資料類型 conference
DOI http://dx.doi.org/10.1145/2009916.2010084
dc.contributor 資訊科學系
dc.creator (作者) Li, Cheng-Te;Lin, Shou-De;Shan, Man-Kwan
dc.creator (作者) 沈錳坤zh_TW
dc.date (日期) 2011-07
dc.date.accessioned 27-Aug-2015 17:34:14 (UTC+8)-
dc.date.available 27-Aug-2015 17:34:14 (UTC+8)-
dc.date.issued (上傳時間) 27-Aug-2015 17:34:14 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/78006-
dc.description.abstract (摘要) Social networking services possess two features: (1) capturing the social relationships among people, represented by the social network, and (2) allowing users to express their preferences on different kinds of items (e.g. photo, celebrity, pages) through endorsing buttons, represented by a kind of endorsement bipartite graph. In this work, using such information, we propose a novel recommendation method, which leverages the viral marketing in the social network and the wisdom of crowds from endorsement network. Our recommendation consists of two parts. First, given some query terms describing user`s preference, we find a set of targeted influencers who have the maximum activation probability on those nodes related to the query terms in the social network. Second, based on the derived targeted influencers as key experts, we recommend items via the endorsement network. We conduct the experiments on DBLP co-authorship social network with author-reference data as the endorsement network. The results show our method can achieve effective recommendations.
dc.format.extent 549827 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) SIGIR `11 Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval,1131-1132
dc.subject (關鍵詞) endorsement network;recommendation;social influence;social network
dc.title (題名) Exploiting endorsement information and social influence for item recommendation
dc.type (資料類型) conferenceen
dc.identifier.doi (DOI) 10.1145/2009916.2010084
dc.doi.uri (DOI) http://dx.doi.org/10.1145/2009916.2010084