文章基本信息

标题：A Study of Web Log Analysis Using Clustering Techniques
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作者：HEMANSHU RANA ; MAYANK PATEL
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2013
卷号：1
期号：4
出版社：S&S Publications
摘要：Web usage mining is the area of web mining which deals with the extraction of interesting knowledge fromweb log information produced by web servers. Web usage mining techniques can be applied for web log analysis. Webaccess data, traditionally, are stored in the server log files. Several web usage mining approaches have been presentedfor exposing usage patterns with the most prominent ones being clustering, association rule, and sequential patternmining. In this paper, three different algorithms are reviewed for generating clusters. The first one is simple K-means,second K-means using Neural Network concept and Self Organization Map (SOM). , This paper deals with study of atwo-stage method that integrates algorithms, first of which uses Self-Organizing Feature Maps neural network todetermine the number of clusters and cluster centroids, then the second one is a K-means algorithm to find the finalsolution
关键词：Web-log analysis; Clustering; K-means; SOM; Neural Network