eprintid: 2839
rev_number: 12
eprint_status: archive
userid: 69
dir: disk0/00/00/28/39
datestamp: 2015-11-06 10:56:49
lastmod: 2016-04-06 10:36:53
status_changed: 2015-11-06 10:56:49
type: article
metadata_visibility: show
creators_name: Cimini, Giulio
creators_name: Medo, Matúš
creators_name: Zhou, Tao
creators_name: Wei, Dong
creators_name: Zhang, Yi-Cheng
creators_id: giulio.cimini@imtlucca.it
creators_id: 
creators_id: 
creators_id: 
creators_id: 
title: Heterogeneity, quality, and reputation in an adaptive recommendation model
ispublished: pub
subjects: H1
subjects: QC
divisions: EIC
full_text_status: public
keywords: Physics and society, Social and information networks
abstract: 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.
date: 2011
date_type: published
publication: The European Physical Journal B - Condensed Matter
volume: 80
number: 2
publisher: Springer
pagerange: 201-208
id_number: 10.1140/epjb/e2010-10716-5
refereed: TRUE
issn: 1434-6028
official_url: http://dx.doi.org/
citation:   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)  
document_url: http://eprints.imtlucca.it/2839/1/1012.1099v1.pdf