Mining characteristics of network community user group based on CDFP-tree algorithm

To ensure the sustainable development of the Internet community, satisfy the demand for the network user's access, this paper introduces how to use the K-means algorithm to divide the network community user group and improve the FP-tree algorithm (CDFP-tree) to analyse the characteristics of the network user group. The purpose is to explore the relationship between the user group's interest, purpose and the natural attribute. The result will be the technical support for the personalized network services. Another focus of this paper is placed on optimizing and improving the FP-tree algorithm which is based on the constraint item, mainly through the adjustment of the method of construction tree and traverse of the trees to realize. The experiments show that comparing to the original algorithm, the CDFP-tree has the same accuracy while the efficiency is highly improved. And the results of the characteristic analysis have a referenced value to the personalized recommendation service.