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Research and Application of Clustering Algorithm Based Web Log Mining

Author: ZhuangZuoZuo
Tutor: CaoQiYing
School: Donghua University
Course: Computer Software and Theory
Keywords: Cluster analysis Fuzzy C-Means Clustering Rough Set Web log mining
CLC: TP311.13
Type: Master's thesis
Year: 2011
Downloads: 74
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Abstract


The data mining process of extracting information from large amounts of data, or \In the realization of the process of data mining, clustering is one of the commonly used methods, clustering analysis has become a very active research topic in the field of data mining research. Cluster analysis used in the mining of Web server logs, records a log of user browsing behavior on the site to extract user access patterns, such as the frequency of page views, user clustering. This knowledge will help website designers to optimize the site topology to provide personalized, intelligent services and improve the performance of your website. From the study of the basic algorithm of cluster analysis, analysis and hierarchical clustering algorithm, k-means clustering algorithm and fuzzy C-means clustering algorithm on the basis of the number of clusters and cluster centers aspects of the algorithm, the improved effectiveness of the algorithm description experiments, and improved algorithm is applied to quality courses Donghua University website log mining, the analysis results. The paper's main work is as follows: 1) analysis and basic clustering algorithm based on the use of standard data sets comparative description of the basic algorithm, and the hierarchical clustering algorithm, k-means clustering algorithm and fuzzy C-means clustering algorithm clustering results were compared. 2) to optimize the design for the initial cluster centers and the number of clusters in the clustering algorithm to improve the algorithm, fuzzy C-means clustering algorithm, the number of clusters estimation methods as well as the Pearson correlation coefficient distance metric method, and further proposed a fuzzy C-means clustering algorithm based on rough set of improvements, and then achieve improved optimization algorithm, fuzzy C-means clustering algorithm are compared with traditional clustering and experimental analysis, compare clustering results improved with traditional algorithms, the effectiveness of the algorithm. 3) The improved algorithm is applied to Web log mining, clustering results of analysis and research, and applications on the Web log data in the of Donghua University boutique course website improved clustering algorithm log analysis studies, found that users of the behavioral characteristics of web page views given site optimization suggestions for improvement.

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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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