Extracting Patterns in Social Network by Means of Link Mining

Abstract

The World Wide Web serves as a huge, widely distributed, global information service center for news, advertisements, consumer information, financial management, education, government, e-commerce, and many other information services. The Web contains a rich and dynamic collection of hyperlink information which can access usage information and provide rich sources for data mining. It is a highly dynamic information source and web service centers update their web pages regularly. Linkage information and access are also updated frequently. This framework is the distillation of broad search topics, through the discovery of “authoritative” information sources on topics. This using hubs, called HITS (Hyperlink-Induced Topic Search) to find authoritative pages based on the relationship between a set of relevant authoritative pages and the set of “hub pages” that join them together in the link structure. This formulation has connections to the eigenvectors of certain matrices associated with the link graph. This HITS algorithm provides surprisingly good search results for a wide range of query.