Tag-based resource recommendation in social annotation applications

  • Authors:
  • Jonathan Gemmell;Thomas Schimoler;Bamshad Mobasher;Robin Burke

  • Affiliations:
  • Center for Web Intelligence, School of Computing, DePaul University, Chicago, Illinois;Center for Web Intelligence, School of Computing, DePaul University, Chicago, Illinois;Center for Web Intelligence, School of Computing, DePaul University, Chicago, Illinois;Center for Web Intelligence, School of Computing, DePaul University, Chicago, Illinois

  • Venue:
  • UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
  • Year:
  • 2011

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Abstract

Social annotation systems enable the organization of online resources with user-defined keywords. The size and complexity of these systems make them excellent platforms for the application of recommender systems, which can provide personalized views of complex information spaces. Many researchers have concentrated on the important problem of tag recommendation. Less attention has been paid to the recommendation of resources in the context of social annotation systems. In this paper, we examine the specific case of tag-based resource recommendation and propose a linear-weighted hybrid for the task. Using six real world datasets, we show that our algorithm is more effective than other more mathematically complex techniques.