Volume 88, Number 3, November 2009
|Number of page(s)||6|
|Section||Interdisciplinary Physics and Related Areas of Science and Technology|
|Published online||12 November 2009|
Adaptive model for recommendation of news
Physics Department, University of Fribourg - CH-1700 Fribourg, Switzerland
2 Department of Modern Physics, University of Science and Technology of China - Hefei 230026, PRC
Accepted: 15 October 2009
Most news recommender systems try to identify users' interests and news' attributes and use them to obtain recommendations. Here we propose an adaptive model which combines similarities in users' rating patterns with epidemic-like spreading of news on an evolving network. We study the model by computer agent-based simulations, measure its performance and discuss its robustness against bias and malicious behavior. Subject to the approval fraction of news recommended, the proposed model outperforms the widely adopted recommendation of news according to their absolute or relative popularity. This model provides a general social mechanism for recommender systems and may find its applications also in other types of recommendation.
PACS: 89.65.-s – Social and economic systems / 89.75.Hc – Networks and genealogical trees / 89.20.Ff – Computer science and technology
© EPLA, 2009
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.