User and Document Group Approach of Clustering in Tagging Systems

Rong Pan, Guandong Xu, Peter Dolog

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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In this paper, we propose a spectral clustering approach for users and documents group modeling in order to capture the common preference and relatedness of users and documents, and to reduce the time complexity of similarity calculations. In experiments, we investigate the selection of the optimal amount of clusters. We also show a reduction of the time consuming in calculating the similarity for the recommender systems by selecting a centroid first, and then compare the inside item on behalf of each group.
Original languageEnglish
Title of host publicationProceeding of The 18th Intl. Workshop on Personalization and Recommendation on the Web and Beyond
PublisherUniversity of Kassel
Publication dateOct 2010
Publication statusPublished - Oct 2010
EventLWA 2010 - Kassel, Germany
Duration: 4 Oct 20106 Oct 2010


ConferenceLWA 2010

Bibliographical note

title={{User and Document Group Approach of Clustering in Tagging Systems}},
author={Pan, R. and Xu, G. and Dolog, P.}


  • User Profile
  • Document Profile
  • Spectral Clustering
  • Group Profile
  • Modularity Metric


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