Design And Realization Of Intelligent Website Based On K-Means Clustering

At present, the development of Internet and e-commerce drives the research for data mining technology facing web. In personalized recommendation system, the user's browsing behavior can be discovered by applying data mining technology on web data such as server logs, and the general knowledge of the group user's behaviors and patterns can be obtained by analyzing the user's accessing behavior and accessing time. In addition, the page structure, the service and marketing strategies can be modified and improved dynamically according to the discovered knowledge to serve the user well and promote the overall quality of the website.Web mining technology makes people can fully find out the relation between the web pages, and the connection between the web organizational forms of website and the access mode of the customer. Among them, the web log mining technology gets the concern of numerous researchers especially. By utilizing the web log mining, we can know the browsing pattern browsing custom as well as browsing behavior of the customer, find the similar user group according to browser behaviors and divide the pages with the same characteristic into groups by the web pages visited by the user.This paper proposed the basic construction of the intellectualized website which can offer the personalized recommendation to the user in real time by mining the Web log and according to the current user's visit behavior on the basis of fully analyzing the research of present situation in the domestic and foreign. This paper has done the thorough careful research to key technologies specially; the primary content is as follows:(1) Proposed a method of obtaining user's interests by mining web log implicitly.(2) Improved the K-Means clustering algorithm, the new algorithm realizes automatically cluster, which improves cluster validity without background knowledge and can be implemented to cluster users. On the basis of the research of the key technologies, this paper proposed the solution to improve the web quality of service, and realized the intellectualized prototype system to provide real-time recommendation based on the user's visit pattern, simultaneously applied the key technologies to the LPQF campus culture website, and obtained good effect.This paper researched the intellectualized prototype system and analyzed the experimental result, which has important instruction and significant impetus to drive the intellectualized website from fundamental theory research to reality application.