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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/78006


    Title: Exploiting endorsement information and social influence for item recommendation
    Authors: Li, Cheng-Te;Lin, Shou-De;Shan, Man-Kwan
    沈錳坤
    Contributors: 資訊科學系
    Keywords: endorsement network;recommendation;social influence;social network
    Date: 2011-07
    Issue Date: 2015-08-27 17:34:14 (UTC+8)
    Abstract: 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.
    Relation: SIGIR '11 Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval,1131-1132
    Data Type: conference
    DOI link: http://dx.doi.org/10.1145/2009916.2010084
    DOI: 10.1145/2009916.2010084
    Appears in Collections:[Department of Computer Science ] Proceedings

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