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Self-organizing Distributed Collaborative Filtering by Jun Wang; Marcel J. T. Reinders; Reginald L. Lagendijk; Johan Pouwelse is a scholarly article available to read on EtoBox.

What is Self-organizing Distributed Collaborative Filtering about?

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 peerto-peer networks.

Author

Jun Wang; Marcel J. T. Reinders; Reginald L. Lagendijk; Johan Pouwelse

Publisher

ACM

Published

2005

Language

EN