eprintid: 2840
rev_number: 7
eprint_status: archive
userid: 69
dir: disk0/00/00/28/40
datestamp: 2015-11-06 11:01:14
lastmod: 2015-11-06 11:01:14
status_changed: 2015-11-06 11:01:14
type: article
metadata_visibility: show
creators_name: Wei, Dong
creators_name: Zhou, Tao
creators_name: Cimini, Giulio
creators_name: Wu, Pei
creators_name: Liu, Weiping
creators_name: Zhang, Yi-Cheng
creators_id: 
creators_id: 
creators_id: giulio.cimini@imtlucca.it
creators_id: 
creators_id: 
creators_id: 
title: Effective mechanism for social recommendation of news
ispublished: pub
subjects: QC
divisions: EIC
full_text_status: public
keywords: Adaptive networks
abstract: Recommender systems represent an important tool for news distribution on the Internet. In this work we modify a recently proposed social recommendation model in order to deal with no explicit ratings of users on news. The model consists of a network of users which continually adapts in order to achieve an efficient news traffic. To optimize the network’s topology we propose different stochastic algorithms that are scalable with respect to the network’s size. Agent-based simulations reveal the features and the performance of these algorithms. To overcome the resultant drawbacks of each method we introduce two improved algorithms and show that they can optimize the network’s topology almost as fast and effectively as other not-scalable methods that make use of much more information.
date: 2011
date_type: published
publication: Physica A: Statistical Mechanics and its Applications
volume: 390
number: 11
publisher: Elsevier
pagerange: 2117 - 2126
id_number: 10.1016/j.physa.2011.02.005
refereed: TRUE
issn: 0378-4371
official_url: http://www.sciencedirect.com/science/article/pii/S0378437111001130
citation:   Wei, Dong and Zhou, Tao and Cimini, Giulio and Wu, Pei and Liu, Weiping and Zhang, Yi-Cheng  Effective mechanism for social recommendation of news.  Physica A: Statistical Mechanics and its Applications, 390 (11).  2117 - 2126.  ISSN 0378-4371      (2011)  
document_url: http://eprints.imtlucca.it/2840/1/1103.5120v2.pdf