Abstract

With the rise of network technology, the Internet has been integrated into all aspects of people’s life, which brings convenience to our daily life. However, the rise of the network has led to the emergence of a large number of web pages, which also makes it difficult for people to accurately need the information. At the same time, the proliferation of Internet users leads to a large number of user behavior data, which has been applied to analyze user behavior. By mining Web log information, we can extract the behavior rules and interests of users, which will put forward more decision direction. By improving the system platform, we can improve better user service, which will improve the user experience. Facing the marine user behavior generated by web, we can analyze it by clustering algorithm, which will better analyze the compliance detection of user behavior. Through user behavior clustering, we can extract the user’s browsing behavior in the web server log, which will better mine the user’s interest.

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