Bayesian network based business information retrieval model |
| |
| Authors: | Zheng Wang Qing Wang Ding-Wei Wang |
| |
| Affiliation: | (1) Department of System Engineering, School of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, 110004, People’s Republic of China |
| |
| Abstract: | 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.
|
| |
| Keywords: | Business information retrieval Bayesian network Belief network Inference network |
| 本文献已被 SpringerLink 等数据库收录！ |
