TY  - JOUR
Y1  - 2011///
A1  - Wei, Dong
A1  - Zhou, Tao
A1  - Cimini, Giulio
A1  - Wu, Pei
A1  - Liu, Weiping
A1  - Zhang, Yi-Cheng
UR  - http://www.sciencedirect.com/science/article/pii/S0378437111001130
VL  - 390
KW  - Adaptive networks
AV  - public
TI  - Effective mechanism for social recommendation of news
SP  - 2117 
JF  - Physica A: Statistical Mechanics and its Applications
PB  - Elsevier
IS  - 11
SN  - 0378-4371
EP  -  2126
ID  - eprints2840
N2  - 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.
ER  -