An Intelligent Search Model Based On Bayesian Network

Nowadays, for the Internet user, finding some relevant information from a large collection of data on the web sites is not an easy task, since many users are frequently faced with a huge alternative links. Hence it would be useful for these users if they were provided with a tool that can assist them in performing the information searching processes.Most existing information searching systems attempt to analyze the content and structural properties of documents, without considering the actual information needs of users explicitly. However, a vast amount of task-specific knowledge is implicitly encoded in the behavior of users accessing an online information col lection. This paper puts forward a documenet search system model based on the user access pattern. With reading time, access frequency, input query string of user, this model applies Bayesian Network to analyze what is the user' s actual interest, and rearranges the result list dynamically. It will make information searching simpler and more efficient.The paper states the whole procedure that how this model is bui It and the principle it is based on detailly. The first two sections give an account of the background knowledge and some work done by other researchers. The next section is about the preparation of data source, and the third tells how the association rules, which is called user access pattern too, are discovered, the fourth section narrates how the user' s actual interest is inferred, and the last section focuses on the performance of the model.