Symmetrical and overloaded effect of diffusion in information filtering

Xuzhen Zhu, Hui Tian, Guilin Chen and Shimin Cai

Physica A: Statistical Mechanics and its Applications, 2017, vol. 483, issue C, 9-15

Abstract: In physical dynamics, mass diffusion theory has been applied to design effective information filtering models on bipartite network. In previous works, researchers unilaterally believe objects’ similarities are determined by single directional mass diffusion from the collected object to the uncollected, meanwhile, inadvertently ignore adverse influence of diffusion overload. It in some extent veils the essence of diffusion in physical dynamics and hurts the recommendation accuracy and diversity. After delicate investigation, we argue that symmetrical diffusion effectively discloses essence of mass diffusion, and high diffusion overload should be published. Accordingly, in this paper, we propose an symmetrical and overload penalized diffusion based model (SOPD), which shows excellent performances in extensive experiments on benchmark datasets Movielens and Netflix.

Keywords: Popularity mining; Popularity control; Collaborative recommendation; Complex network (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:483:y:2017:i:c:p:9-15

DOI: 10.1016/j.physa.2017.04.087

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