%0 Journal Article %1 keyhere %A Xie, Bo %A Han, Peng %A Yang, Fan %A Shen, Ruimin %D 2004 %J Database and Expert Systems Applications %K cf neighborhood peer-to-peer unread %P 141--150 %T An Efficient Neighbor Searching Scheme of Distributed Collaborative Filtering on P2P Overlay Network %U http://www.springerlink.com/content/x5c90xmxeqhy4gb0 %X Distributed Collaborative Filtering (DCF) has gained more and more attention as an alternative implementation scheme of CF based recommender system, because of its advantage in scalability and privacy protection. However, as the re is no central user database in DCF systems, the task of neighbor searching becomes much more difficult. In this paper, we first propose an efficient distributed user profile management scheme based on distributed hash table (DHT) method, which is one of the most popular and effective routing algorithm in Peer-to-Peer (P2P) overlay network. Then, we present a heuristic neighbor searching algorithm to locate potential neighbors of the active users in order to reduce the network traffic and executive cost. The experimental data show that our DCF algorithm with the neighbor searching scheme has much better scalability than traditional centralized ones with comparable prediction efficiency and accuracy. ER -

@article{keyhere, abstract = {Distributed Collaborative Filtering (DCF) has gained more and more attention as an alternative implementation scheme of CF based recommender system, because of its advantage in scalability and privacy protection. However, as the re is no central user database in DCF systems, the task of neighbor searching becomes much more difficult. In this paper, we first propose an efficient distributed user profile management scheme based on distributed hash table (DHT) method, which is one of the most popular and effective routing algorithm in Peer-to-Peer (P2P) overlay network. Then, we present a heuristic neighbor searching algorithm to locate potential neighbors of the active users in order to reduce the network traffic and executive cost. The experimental data show that our DCF algorithm with the neighbor searching scheme has much better scalability than traditional centralized ones with comparable prediction efficiency and accuracy. ER -}, added-at = {2007-10-09T11:48:42.000+0200}, author = {Xie, Bo and Han, Peng and Yang, Fan and Shen, Ruimin}, biburl = {https://www.bibsonomy.org/bibtex/2ba477b87a1c277df26fe28d5621adeb9/viv}, description = {SpringerLink - Buchkapitel}, interhash = {aa5f27b16efef68c3f881036d3fc2b80}, intrahash = {ba477b87a1c277df26fe28d5621adeb9}, journal = {Database and Expert Systems Applications}, keywords = {cf neighborhood peer-to-peer unread}, pages = {141--150}, timestamp = {2008-01-23T16:14:41.000+0100}, title = {An Efficient Neighbor Searching Scheme of Distributed Collaborative Filtering on P2P Overlay Network}, url = {http://www.springerlink.com/content/x5c90xmxeqhy4gb0}, year = 2004 }