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Chin. Phys. B, 2015, Vol. 24(7): 078901    DOI: 10.1088/1674-1056/24/7/078901

An improved recommendation algorithm via weakening indirect linkage effect

Chen Guang (陈光), Qiu Tian (邱天), Shen Xiao-Quan (沈小泉)
School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China
Abstract  We propose an indirect-link-weakened mass diffusion method (IMD), by considering the indirect linkage and the source object heterogeneity effect in the mass diffusion (MD) recommendation method. Experimental results on the MovieLens, Netflix, and RYM datasets show that, the IMD method greatly improves both the recommendation accuracy and diversity, compared with a heterogeneity-weakened MD method (HMD), which only considers the source object heterogeneity. Moreover, the recommendation accuracy of the cold objects is also better elevated in the IMD than the HMD method. It suggests that eliminating the redundancy induced by the indirect linkages could have a prominent effect on the recommendation efficiency in the MD method.
Keywords:  bipartite network      mass diffusion      recommender system      indirect linkage effect  
Received:  24 October 2014      Revised:  02 February 2015      Accepted manuscript online: 
PACS:  89.75.Hc (Networks and genealogical trees)  
  87.23.Ge (Dynamics of social systems)  
  05.70.Ln (Nonequilibrium and irreversible thermodynamics)  
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 11175079) and the Young Scientist Training Project of Jiangxi Province, China (Grant No. 20133BCB23017).
Corresponding Authors:  Qiu Tian     E-mail:

Cite this article: 

Chen Guang (陈光), Qiu Tian (邱天), Shen Xiao-Quan (沈小泉) An improved recommendation algorithm via weakening indirect linkage effect 2015 Chin. Phys. B 24 078901

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