Research on Influence Pattern for Internet Association Relation Monitoring

The Internet shows more about information sharing, communication and freedom from Web to Web 2.0. However, there are challenges on the monitoring the influence structure of the negligible individuals on the web. This paper defines the ¿close relationship¿ between social individuals hidden in variety of communication medias of Internet, designs a novel intelligent association relation mining mechanism for removing the fault influence of non-valuable high frequency to improve the information quality measure of the ¿close relationship¿; also, this paper introduces Interpretive Structural Model (ISM) to explore the power of the influence, the central figures and their close relationships, to discover the pattern and channel for information flow between the social individuals in the network. The model is suitable to relation structure mining in many kinds of networks and medias and to reveal the important relations and their influences in the virtual networks. The experiments on the original data show that the feasibility of the whole model in this paper is satisfactory.