| Popis: |
The analysis of community evolution in dynamic network is one of the current research hotspots, which plays an important role in public opinion control, network marketing, personalized recommendation service and so on. This paper proposes a nonparametric core node detection algorithm based on the evaluation index of node importance, which is used to find the core nodes in the community to form the core node set, and to judge the difference of community based on the core node set. Based on this, a classification model of community evolution based on similarities and differences is proposed. This model determines the evolution relationship and divides the evolution type from the two aspects of similarities and differences. Comparing the proposed classification model with GED and SGCI in HEP-TH and Polish political blogosphere data sets, the experimental results show that the proposed classification model is better than GED and SGCI classification model on the whole. Especially in the detection of forming and dissolving events, it can be sensitive to small communities, and can detect a variety of evolution types of small communities. |
