Web active user website accessing mode on-line excavation method

Abstract

The invention discloses an on-line excavation method of a Web active user website access mode. The invention adopts a method of on-line real time identifying the active user and real time excavating user access mode to gain a frequent access mode of the active user for the website. The method is based on a frequent degree mode of an association rule, and only need to scan user request data once so as to real time identify the active user and extract conversation information of the active user. The method adopts a mode of bottom-to-top to generate all subtrees quickly from conversation tree according to characteristics of rooted subtrees, and structures an effective storage structure global Trie tree to maintain the generated subtrees. Algorithm effectively combines a sliding window mode on the base of traditional frequent mode excavation method, so as to real time excavate the frequent access mode of the active user for the website. The invention can real time and quickly analyze and excavate the access mode of the active user for the website, and is an effective and practical user behavior mode analysis method.

Description

technical field [0001] The invention relates to the identification analysis of active website users and the mining technology of frequent access patterns, in particular to an online mining method for website access patterns of active web users. Background technique [0002] With the development of Internet technology, various Internet applications continue to emerge, and Internet users continue to increase. Analyzing the behavior patterns of network users and mining potential users have become a new method to increase the click-through rate of websites and improve the quality of website services. Web mining technology is considered to be an effective method to analyze and mine potential information on the Internet. Generally speaking, Web mining can be divided into: Web content mining, which automatically finds useful information from the Web; Web usage mining, which discovers the user's access characteristics from the user's visit to the website. Web usage mining technolo...

AI Technical Summary

Problems solved by technology

Although these methods can effectively dig out the user's usage pattern of the website, they have the following problems: 1) Since the historical data of the user is used, the analysis is only the historical behavior of the user, and the user information cannot be analyzed in real time. Therefore, the behavior pattern of the current user cannot be accurately given; 2) Since the excavated is a sequence pattern, only the time sequence relationship between the access requests is given, but the logical relationship between the access request pages is not given, some Not even using the organizational structure relationship of the website; 3) These methods generally consider all users, but do not effectively target active users in the website. Generally speaking, the access patterns of active users are often inconsistent with ordinary users

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