Research And Application Of Data Mining For Intelligent Website

At present, the development of Internet and e-commerce drives the research for data mining technology facing web. In e-Commerce, 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 customer'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 make the electronic commercial activity more pointed.Web mining technology make people can fully find out the relation of 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 the numerous researchers especially. By utilizing web log mining, we can know the browser mode 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.On the basis of discussion above, the solution to improve the quality of website service putting forward in the article is adopting web log mining technology of data mining as key technology to establish a intelligent website (Intelligent Web Site, abbreviated as IWS). Intelligent website utilizes web logs, files, database, website structure, and other data resources that may win to obtain user's accessing pattern by adopting data mining technology, and according to the situation which users visit at present, recommend the content that users might interested in real-time, besides, web server according to operating position of website, look for unreasonable place that website design, thus remind administrators to revise.In this paper, we propose structure and composition module of the IWS at first, and study some data mining algorithm, and then realize one prototype system on this basis finally. According to this, the paper includes the contents as follows: The second chapter puts forward the design standard and architecture of intelligent website based on web log mining as an index of follow-up content of thesis. Chapter 3 mainly introduces a method to improve the data preprocessing of the web log mining, that is Frame page filter technology. The 4th chapter expounds one fast high-efficient cluster pattern algorithm to mine web log ?SLIC. Chapter 5 proposes a strengthening algorithm of frequently accessing web page group in web log mining. The 6th part discusses the real-time recommendation module and administrator's module for intelligence website based on web log mining. According to ahead discussion, 7 part give and publish one test prototype system -IWS, the last chapter summarizes research work of this dissertation and further researches are prospected.