Heterogeneity, quality, and reputation in an adaptive recommendation model

被引：20

作者：

Cimini, G. ^{[1
]}

Medo, M. ^{[1
]}

Zhou, T. ^{[1
,2
,3
]}

Wei, D. ^{[1
]}

Zhang, Y. -C. ^{[1
]}

机构：

[1] Univ Fribourg, Dept Phys, CH-1700 Fribourg, Switzerland

[2] Univ Elect Sci & Technol China, Web Sci Ctr, Chengdu 610054, Peoples R China

[3] Univ Sci & Technol China, Dept Modern Phys, Hefei 230026, Peoples R China

来源：

EUROPEAN PHYSICAL JOURNAL B | 2011年 / 80卷 / 02期

关键词：

NETWORKS; SYSTEMS;

D O I：

10.1140/epjb/e2010-10716-5

中图分类号：

O469 [凝聚态物理学];

学科分类号：

070205 ;

摘要：

Recommender systems help people cope with the problem of information overload. A recently proposed adaptive news recommender model [M. Medo, Y.-C. Zhang, T. Zhou, Europhys. Lett. 88, 38005 (2009)] is based on epidemic-like spreading of news in a social network. By means of agent-based simulations we study a "good get richer" feature of the model and determine which attributes are necessary for a user to play a leading role in the network. We further investigate the filtering efficiency of the model as well as its robustness against malicious and spamming behaviour. We show that incorporating user reputation in the recommendation process can substantially improve the outcome.

引用

页码：201 / 208

页数：8

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