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Using approximate inference techniques, we investigate in this paper the applicability of Bayesian Networks to the problem of ranking a large set of documents. Topology of the network is a bipartite. Network parameters (conditional probability distributions) are determined through an adoption of the weighting scheme tf -idf . Rank of a document with respect to a given query is defined as the corresponding posterior probability, which is estimated through performing Rejection Sampling.doi:10.1145/2911451.2914750 dblp:conf/sigir/TanHA16 fatcat:gl2umv2kjnhb3jv2fyoymstkvm