relation: http://eprints.imtlucca.it/2839/
title: Heterogeneity, quality, and reputation in an adaptive recommendation model
creator: Cimini, Giulio
creator: Medo, Matúš
creator: Zhou, Tao
creator: Wei, Dong
creator: Zhang, Yi-Cheng
subject: H Social Sciences (General)
subject: QC Physics
description: 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.
publisher: Springer
date: 2011
type: Article
type: PeerReviewed
format: application/pdf
language: en
rights: cc_by_nc
identifier: http://eprints.imtlucca.it/2839/1/1012.1099v1.pdf
identifier:   Cimini, Giulio and Medo, Matúš and Zhou, Tao and Wei, Dong and Zhang, Yi-Cheng  Heterogeneity, quality, and reputation in an adaptive recommendation model.  The European Physical Journal B - Condensed Matter, 80 (2).  pp. 201-208.  ISSN 1434-6028      (2011)  
relation: http://dx.doi.org/
relation: 10.1140/epjb/e2010-10716-5