Social Tag-based Community Recommendation Using Latent Semantic Analysis

FieldValue
dc.contributor.authorAkther, Aysha
dc.date.accessioned2012-09-07T12:33:30Z
dc.date.available2012-09-07T12:33:30Z
dc.date.created2012
dc.date.issued2012
dc.identifier.urihttp://hdl.handle.net/10393/23238
dc.identifier.urihttp://dx.doi.org/10.20381/ruor-5983
dc.description.abstractCollaboration 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.
dc.language.isoen
dc.publisherUniversité d'Ottawa / University of Ottawa
dc.subjectCommunity Recommendations
dc.subjectLatent Semantic Analysis
dc.subjectRecommender Systems
dc.subjectSocial Community
dc.titleSocial Tag-based Community Recommendation Using Latent Semantic Analysis
dc.typeThesis
dc.faculty.departmentScience informatique et génie électrique / Electrical Engineering and Computer Science
dc.contributor.supervisorEl Saddik, Abdulmotaleb
dc.embargo.termsimmediate
dc.degree.nameMCS
dc.degree.levelmasters
dc.degree.disciplineGénie / Engineering
thesis.degree.nameMCS
thesis.degree.levelMasters
thesis.degree.disciplineGénie / Engineering
uottawa.departmentScience informatique et génie électrique / Electrical Engineering and Computer Science
CollectionThèses, 2011 - // Theses, 2011 -

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