Research Of Web Log Mining Technology On Admissions Information Network

With the continuous development of Internet technology and the widespread popularity of network applications, Web sites have a wealth of information resources, which also contributed to the research and application of Web data mining technology. As one of the important research areas in a Web data mining, Web log mining is the use of data mining techniques to find behavior patterns of Web user in Web logging. In addition to the server’s log records, Web log also includes the interaction between the user and the site of the proxy server logs, browser-side logs, and cookie information. It is by digging through a large number of users and path information recorded in Web log data that it plays important role on the ability and reality to get the user’s access mode, personalize information services, improve site design and build intelligent Web site.Based on Web log from Admissions Information Network in College of Applied Arts and Science of Beijing Union University, this paper concerns search on applications in association rule mining in the Web log mining to find the user’s access mode from the Admissions Information Web logging excavation site and the potential demand. Web log data preprocessing by research theories and methods, combined with the Admissions Information Network site structural features were designed data cleaning, user identification, session identification and other aspects of the algorithm, and the algorithm log into the Web mining algorithms can identify of data sets; through the study of the theory and methods of the Web log mining association rules, the establishment of an association rule mining system, and use the system analyzes the threshold setting on the mining results to find the appropriate mining model, the realization of Admissions information Web log information for mining association rules; By studying the basic ideas and methods of the clustering mining and using k-means algorithm, cluster these users with similar interests, based on that access to Admissions Information Network.