Mean Field Approach to a Probabilistic Model in Information Retrieval

Part of Advances in Neural Information Processing Systems 15 (NIPS 2002)

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Bin Wu, K. Wong, David Bodoff


We study an explicit parametric model of documents, queries, and rel- evancy assessment for Information Retrieval (IR). Mean-field methods are applied to analyze the model and derive efficient practical algorithms to estimate the parameters in the problem. The hyperparameters are es- timated by a fast approximate leave-one-out cross-validation procedure based on the cavity method. The algorithm is further evaluated on several benchmark databases by comparing with standard algorithms in IR.