A generalized model via random walks for information filtering

被引:6
|
作者
Ren, Zhuo-Ming [1 ,2 ]
Kong, Yixiu [1 ]
Shang, Ming-Shang [2 ]
Zhang, Yi-Cheng [1 ]
机构
[1] Univ Fribourg, Dept Phys, Chemin Musee 3, CH-1700 Fribourg, Switzerland
[2] Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
基金
瑞士国家科学基金会; 中国国家自然科学基金;
关键词
Information filtering; Recommendations; Random walk;
D O I
10.1016/j.physleta.2016.06.009
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
There could exist a simple general mechanism lurking beneath collaborative filtering and interdisciplinary physics approaches which have been successfully applied to online E-commerce platforms. Motivated by this idea, we propose a generalized model employing the dynamics of the random walk in the bipartite networks. Taking into account the degree information, the proposed generalized model could deduce the collaborative filtering, interdisciplinary physics approaches and even the enormous expansion of them. Furthermore, we analyze the generalized model with single and hybrid of degree information on the process of random walk in bipartite networks, and propose a possible strategy by using the hybrid degree information for different popular objects to toward promising precision of the recommendation. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:2608 / 2614
页数:7
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