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The quality of business information can significantly affect the operation level of enterprise. This paper analyses the problem of business information retrieval (BIR). A Bayesian Network Based business information retrieval model (BN-BIRM) is proposed by means of Bayesian network (BN) and information retrieval (IR) theory and a method for query adaptation is presented. In this model the customized query requirement of enterprise (CQR) is expressed in terms of the predefined illustrative documents related to business domain. The similarities between the documents and the query are evaluated with the conditional probabilities among the nodes in the BN. In the experiments, BN-BIRM is compared with the Belief Network model based on vector space model (VSM) ranking strategy and the Inference Network model based on TF-IDF ranking strategy. The experimental results show that BN-BIRM is effective for collecting business information on a large scale.