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