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Social Tag-based Community Recommend...
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Akther, Aysha.
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Social Tag-based Community Recommendation using Latent Semantic Analysis.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Social Tag-based Community Recommendation using Latent Semantic Analysis./
作者:
Akther, Aysha.
面頁冊數:
79 p.
附註:
Source: Masters Abstracts International, Volume: 51-06.
Contained By:
Masters Abstracts International51-06(E).
標題:
Computer science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR86932
ISBN:
9780494869321
Social Tag-based Community Recommendation using Latent Semantic Analysis.
Akther, Aysha.
Social Tag-based Community Recommendation using Latent Semantic Analysis.
- 79 p.
Source: Masters Abstracts International, Volume: 51-06.
Thesis (M.C.Sc.)--University of Ottawa (Canada), 2012.
Collaboration and sharing of information are the basis of modern social web system. Users in the social web systems are establishing and joining online communities, in order to collectively share their content with a group of people having common topic of interest. Group or community activities have increased exponentially in modern social Web systems. With the explosive growth of social communities, users of social Web systems have experienced considerable difficulty with discovering communities relevant to their interests. In this study, we address the problem of recommending communities to individual users. Recommender techniques that are based solely on community affiliation, may fail to find a wide range of proper communities for users when their available data are insufficient. We regard this problem as tag-based personalized searches. Based on social tags used by members of communities, we first represent communities in a low-dimensional space, the so-called latent semantic space, by using Latent Semantic Analysis. Then, for recommending communities to a given user, we capture how each community is relevant to both user's personal tag usage and other community members' tagging patterns in the latent space. We specially focus on the challenging problem of recommending communities to users who have joined very few communities or having no prior community membership. Our evaluation on two heterogeneous datasets shows that our approach can significantly improve the recommendation quality.
ISBN: 9780494869321Subjects--Topical Terms:
523869
Computer science.
Social Tag-based Community Recommendation using Latent Semantic Analysis.
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