Table of Contents Author Guidelines Submit a Manuscript
The Scientific World Journal
Volume 2014 (2014), Article ID 295931, 14 pages
http://dx.doi.org/10.1155/2014/295931
Research Article

A Collaborative Recommend Algorithm Based on Bipartite Community

1Suzhou Industrial Park Institute of Services Outsourcing, Suzhou, Jiangsu 215123, China
2School of Computer Science and Technology, Soochow University, Suzhou, Jiangsu 215006, China

Received 31 August 2013; Accepted 17 November 2013; Published 13 April 2014

Academic Editors: Y. Lu and F. Yu

Copyright © 2014 Yuchen Fu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The recommendation algorithm based on bipartite network is superior to traditional methods on accuracy and diversity, which proves that considering the network topology of recommendation systems could help us to improve recommendation results. However, existing algorithms mainly focus on the overall topology structure and those local characteristics could also play an important role in collaborative recommend processing. Therefore, on account of data characteristics and application requirements of collaborative recommend systems, we proposed a link community partitioning algorithm based on the label propagation and a collaborative recommendation algorithm based on the bipartite community. Then we designed numerical experiments to verify the algorithm validity under benchmark and real database.