Distributed Customer Tagmeme Evaluation Model Based on the Multi-Attributes Tree Bayesian Network

In this paper, a distributed customer tagmeme evaluation model based on the multi-attributes tree Bayesian network was proposed to solve a distributed customer tagmeme evaluation problem. First, using mobile agents which could visit distributed data-sets, the multi-attributes tree and the Bayesian network were built. Then, all the distributed data-sets were trained by Bayesian network structure learning and parameter learning. By this way, the tagmeme of test samples could be evaluated. Comparing with the traditional customer tagmeme evaluation models, the experiment result showed that the distributed customer tagmeme evaluation model could solve the problems of heavy burden, large storage costs and inefficiency during Bayesian network learning. And this model showed higher forecast precision and better practicability.