Title
An improved HeatS+ProbS hybrid recommendation algorithm based on heterogeneous initial resource configurations
Abstract
Network-based recommendation algorithms for user-object link predictions have achieved significant developments in recent years. For bipartite graphs, the reallocation of resource in such algorithms is analogous to heat spreading (HeatS) or probability spreading (ProbS) processes. The best algorithm to date is a hybrid of the HeatS and ProbS techniques with homogenous initial resource configurations, which fulfills simultaneously high accuracy and large diversity. We investigate the effect of heterogeneity in initial configurations on the HeatS+ProbS hybrid algorithm and find that both recommendation accuracy and diversity can be further improved in this new setting. Numerical experiments show that the improvement is robust.
Year
Venue
Keywords
2010
Clinical Orthopaedics and Related Research
bipartite graph,information retrieval,hybrid algorithm
DocType
Volume
Citations 
Journal
abs/1005.3
8
PageRank 
References 
Authors
0.45
8
2
Name
Order
Citations
PageRank
Chuang Liu1582.21
Wei-Xing Zhou220615.05