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The Research of Frequent Pattern Algorithm Based on Web Log Mining

Author: FengJun
Tutor: ZhengCheng
School: Anhui University
Course: Computer Software and Theory
Keywords: Web log mining Data preprocessing Client log data Page degree of interest The right to frequent access patterns
CLC: TP311.13
Type: Master's thesis
Year: 2011
Downloads: 29
Quote: 0
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Abstract


With the rapid development of the Internet and the rapid proliferation of Web sites has become the manufacturing, publishing, the main platform of the handling and processing of information, but its structure has become increasingly complex in providing people with a lot of information services at the same time, the data on the Web the amount of rapid expansion. How to dig out these large amounts of data potentially useful knowledge and information, to improve the structure of the Web site to facilitate the user's access to the user to provide a better service, thus increasing website profits. To solve these problems, the traditional data mining knowledge and technology will be introduced into the field of Web, Web log data mining process, we can get useful information and patterns which, ultimately, this knowledge will be used for Web site optimization Business Intelligence, to provide users with a personalized service, system performance improvements. This is the Web log mining, which has been the concern of many research scholars client log mining. In this paper, the theoretical knowledge and complete Web log mining process in detail discussed improved methods and innovative ideas combined with theoretical knowledge and practical application of the relevant issues. First, the Web log mining research background, significance and data sources detailed description and specific analysis and detailed, and the pre-treatment process for the Web server-side log data. Focus on detailed knowledge and problem solution on the client Web log, client Web log and server log distinction, then a detailed analysis of the client log data acquisition method. Secondly, in the the client Web log data based on the detailed analysis of the deficiencies of the existing page interest calculation method, calculate the real page time considering page has been accessed frequency and user real time page views , proposed an improved the page degree of interest calculated on the basis of. Through analysis, to improved page interest calculation method is more reasonable and true reflection of the level of interest of the user on the page. And then analyzing the site's configuration diagram page degrees of interest as a weight assigned to the corresponding node in the structure diagram, generating a weighted directed graph. Finally, to generate weighted directed graph and user access transaction database based mining frequent user access patterns, and propose a solution to this problem by improving GTWF algorithm. Algorithm, the use of the right support, the concept of expansion mode and the right to frequent mode algorithm graph traversal patterns mining and pruning operation and candidate mode operation, and finally through experiments verify the performance of the algorithm.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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