2011/02/03 by Dong Wei, Tao Zhou, Giulio Cimini +3
Physics and Astronomy · Computer Science · #physics.soc-ph #cs.SI
paper · pdf · doi:10.1016/j.physa.2011.02.005
published as Physica A, Volume 390, Issue 11, p. 2117-2126 (2011)
arxiv created 2011/02/03 · arxiv updated 2015/05/27
Recommendation 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 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 network's topology almost as fast and effectively as other not-scalable methods that make use of much more information.