Information filtering via Iterative Refinement
arXiv:physics/0608166 · doi:10.1209/epl/i2006-10204-8
Abstract
With the explosive growth of accessible information, expecially on the Internet, evaluation-based filtering has become a crucial task. Various systems have been devised aiming to sort through large volumes of information and select what is likely to be more relevant. In this letter we analyse a new ranking method, where the reputation of information providers is determined self-consistently.
10 pages, 3 figures. Accepted for publication on Europhysics Letters
References in corpus (6)
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