| Recently, with the rapid development of Internet technology, the Internet has gradually become a huge, global information service center. However, various problems come with the increasing amount of information on the Internet. In order to solve these problems, many large web sites have launched personalized services. Personalized services provide different service strategies and models to different web users, which through the web to collect users' information in advance to analyze users'behavior and interests, thereby providing the users' individual requirements. Through the effective mining web data, you can better understand the user's interest, analyze the user's access patterns, provide real-time recommendation according to the user's individual needs.This paper introduces the personalized service, data mining, web data mining and other related concepts, implemented for the current personalized service, an analysis of its meaning of its problems, and played with no way out of the mining process Web data mining and related technologies.Secondly, this paper presents a Web-based data mining system model of personalized service, and an overview of the various parts of features. System can be based on the user's current access behavior, analyze user-mode, the dynamic page for the user recommendation.Then discussed in detail in the Web personalization service system the whole process of data preparation, and gives the key to every step of the algorithm. First, to conduct data collection, and then the moral right to collect Web data pre-processing, including:data cleaning, user identification, session identification, path added and transaction identification.Finally, the theory of association rule mining research, analyzed some of the traditional mining algorithm and its problems and, through its proposed to improve the environment, frequent in the Web access patterns mining algorithm and the method is verified by experiment better performance, improved mining efficiency. |
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