RankMerging: Learning to Rank in Large-Scale Social Networks

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Provided by: RWSoftware
Topic: Networking
Format: PDF
In this paper, the authors consider the issue of unveiling unknown links in a social network, one of the difficulties of this problem being the small number of unobserved links in comparison of the total number of pairs of nodes. They define a simple supervised learning-to-rank framework, called RankMerging, which aims at combining information provided by various unsupervised rankings. As an illustration, they apply the method to the case of a cell phone service provider, which uses the network among its contractors as a learning set to discover links existing among users of its competitors.
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