Effective mechanism for social recommendation of news
- Wei, Dong Physics Department, University of Fribourg, Switzerland
- Zhou, Tao Physics Department, University of Fribourg, Switzerland - Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China - Department of Modern Physics, University of Science and Technology of China, Hefei, China
- Cimini, Giulio Physics Department, University of Fribourg, Switzerland
- Wu, Pei Physics Department, University of Fribourg, Switzerland
- Liu, Weiping Physics Department, University of Fribourg, Switzerland
- Zhang, Yi-Cheng Physics Department, University of Fribourg, Switzerland
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17.02.2011
Published in:
- Physica A: Statistical Mechanics and its Applications. - 2011, vol. 390, no. 11, p. 2117-2126
English
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.
- Faculty
- Faculté des sciences et de médecine
- Department
- Département de Physique
- Language
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- English
- Classification
- Physics
- License
- License undefined
- Identifiers
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- RERO DOC 27340
- DOI 10.1016/j.physa.2011.02.005
- Persistent URL
- https://folia.unifr.ch/unifr/documents/302154
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