Distributed collaborative filtering for peer-to-peer file sharing systems Export

@inproceedings{wang-etal-sac06, abstract = {Collaborative filtering requires a centralized rating database. However, within a peer-to-peer network such a centralized database is not readily available. In this paper, we propose a fully distributed collaborative filtering method that is self-organizing and operates in a distributed way. Similarity ranks between multimedia files (items) are calculated by log-based user profiles and are stored locally at these items in so-called buddy tables . This intuitively creates a semantic overlay to organize multimedia files. Based on this semantic overlay and the items that a user has downloaded previously (indicating the profile of the user), recommendations can be performed and the recommended items can be easily located. We have tested our distributed collaborative filtering approach and compared it to centralized collaborative filtering, showing that it has similar performance. It is therefore a promising technique to facilitate filtering for relevant multimedia data in P2P networks.}, address = {New York, NY, USA}, author = {Wang, Jun and Pouwelse, Johan and Lagendijk, Reginald L. and Reinders, Marcel J. T.}, booktitle = {SAC '06: Proceedings of the 2006 ACM symposium on Applied computing}, citeulike-article-id = {1045988}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1141277.1141522}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1141277.1141522}, doi = {10.1145/1141277.1141522}, isbn = {1-59593-108-2}, keywords = {collaborative, distributed, filtering, p2p}, location = {Dijon, France}, pages = {1026--1030}, posted-at = {2009-11-10 00:49:55}, priority = {2}, publisher = {ACM}, title = {Distributed collaborative filtering for peer-to-peer file sharing systems}, url = {http://dx.doi.org/10.1145/1141277.1141522}, year = {2006} }

TY - CONF ID - wang-etal-sac06 L3 - citeulike-article-id:1045988 N2 - Collaborative filtering requires a centralized rating database. However, within a peer-to-peer network such a centralized database is not readily available. In this paper, we propose a fully distributed collaborative filtering method that is self-organizing and operates in a distributed way. Similarity ranks between multimedia files (items) are calculated by log-based user profiles and are stored locally at these items in so-called buddy tables . This intuitively creates a semantic overlay to organize multimedia files. Based on this semantic overlay and the items that a user has downloaded previously (indicating the profile of the user), recommendations can be performed and the recommended items can be easily located. We have tested our distributed collaborative filtering approach and compared it to centralized collaborative filtering, showing that it has similar performance. It is therefore a promising technique to facilitate filtering for relevant multimedia data in P2P networks. CY - Dijon, France SN - 1-59593-108-2 AD - New York, NY, USA EP - 1030 TI - Distributed collaborative filtering for peer-to-peer file sharing systems PB - ACM T2 - SAC '06: Proceedings of the 2006 ACM symposium on Applied computing SP - 1026 KW - collaborative KW - distributed KW - filtering KW - p2p AU - Wang, Jun AU - Pouwelse, Johan AU - Lagendijk, Reginald AU - Reinders, Marcel PY - 2006/// UR - http://dx.doi.org/10.1145/1141277.1141522 ER -