Improving Collaborative Filtering in Social Tagging Systems

  • Felice Ferrara
  • Carlo Tasso
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7023)


User-based Collaborative Filtering (CF) systems generate recommendations for a specific user by combining feedback (i.e. information about what is relevant for a user) provided by a set of people similar to that user. In these system the similarity among people is computed by taking into account the set of shared resources. However, there are several application domains, such as social tagging systems, where each user may have several different Topic of Interests (ToIs). In these cases, two users could share only some interests and, therefore, only a part of the feedback should be considered for producing recommendations. Focusing on social tagging systems, we propose here a novel approach to detect ToIs in the collection of the bookmarks of a user. Given a specific ToI, we adaptively identify similar people (i.e., sharing the same ToI) and select only the resources relevant to the specific ToI.


Social tagging collaborative filtering adaptive system personalization 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Felice Ferrara
    • 1
  • Carlo Tasso
    • 1
  1. 1.University of UdineUdineItaly

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