文章基本信息

标题：A Method of Discovery of Shared Topic Networks among People from WWW Bookmarks and Its Evaluations
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作者：Masahiro Hamasaki ; Hideaki Takeda ; Takeshi Matsuzuka 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2002
卷号：17
期号：3
页码：276-284
DOI：10.1527/tjsai.17.276
出版社：The Japanese Society for Artificial Intelligence
摘要：In this paper, we propose shared topic networks as a model of human network to organize Internet Information, and developed a system called kMedia that can generate shared topic networks by using WWW bookmark files. We also evaluate the system with experiments to know how shared topics network can help uesrs especially to know each other. A shared topic network is formed by linking topics of participants, and used to know interests of others and to exchange information with others. kMedia can generate shared topics networks by using structures of WWW bookmarks, i.e., folders of bookmarks are regarded as topics of their owners. Relations among topics of different users are estimated by aggregating similarity among pages in these topics. The experiments were performed to clarify two points; one is whether topics is a better way to exchange information among people and the other is how we can measure human relationship. The first point is examined that topic recommendation is more acceptable than page recommendation. For the second point, we propose category resemblance as measurement of human relationship. Since we compare results between cases with subjects belonging to the same community and cases without communities, we noticed similarity of topics structure is affective. The category resemblance is to estimate this similarity of topic structure and it is proved that it is better than any other parameters with respect to measurement for human relationship.
关键词：collaborative filltering ; information retrieval ; recommender system ; world wide web