Research on knowledge cluster based on Bayesian network
基于贝叶斯网的知识集群研究

To address the limitation of traditional knowledge classification model in knowledge service website, it presents a new concept, called knowledge clusters, based on the online access to the item of knowledge according to the view of clustering behavior in Sociology, because we see the user's access behavior of knowledge as clustering behavior. The paper builds a dynamic model of knowledge aggregation, called knowledge cluster model, by regarding accessed item of knowledge as nodes in the Bayesian network and describing the dependencies between the nodes using the probabilistic reasoning method, and then to form the knowledge aggregation dynamically. At last, this model approach is proved to be feasible and valid through the experimental data.