TY  - JOUR
TI  - Heterogeneity, quality, and reputation in an adaptive recommendation model
SP  - 201
AV  - public
KW  - Physics and society
KW  -  Social and information networks
VL  - 80
Y1  - 2011///
UR  - http://dx.doi.org/
A1  - Cimini, Giulio
A1  - Medo, Matú?
A1  - Zhou, Tao
A1  - Wei, Dong
A1  - Zhang, Yi-Cheng
N2  - 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.
EP  - 208
ID  - eprints2839
SN  - 1434-6028
IS  - 2
PB  - Springer
JF  - The European Physical Journal B - Condensed Matter
ER  -