Self-organizing distributed collaborative filtering

Authors:
Jun Wang;Marcel J. T. Reinders;Reginald L. Lagendijk;Johan Pouwelse
Affiliations:
Delft University of Technology, Delft, The Netherlands;Delft University of Technology, Delft, The Netherlands;Delft University of Technology, Delft, The Netherlands;Delft University of Technology, Delft, The Netherlands
Venue:
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2005

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Abstract

We propose a fully decentralized collaborative filtering approach that is self-organizing and operates in a distributed way. The relevances between downloading files (items) are stored locally at these items in so called item-based buddy tables and are updated each time that the items are downloaded. We then propose to use the language model to build recommendations for the different users based on the buddy tables of those items a user has downloaded previously. We have tested and compared our distributed collaborative filtering approach to centralized collaborative filtering and showed that it has similar performance. It is therefore a promising technique to facilitate recommendations in peer-to-peer networks.