期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2016
卷号：92
期号：2
出版社：Journal of Theoretical and Applied
摘要：Information on Internet and specially on website environment is increasing rapidly day by day and become very huge, this information play an important role for discovering various knowledge in the Web. Web Usage Mining one of the Web Mining algorithm categories that concern with discover and analysis useful information regard to link prediction, users' navigation, customers' behavior, site reorganization, web personalization and frequent access patterns from large web data that logs by Web server side and stored in standard text log file format called log file or Web usage data, this data can also be collected from an organization's database such as NASA. Web Usage Mining is a process of applying Data mining techniques and application to analyze and discover interesting knowledge from the Web. There are several existing research works on log file mining, some concern with web site structure, traversal pattern mining, association rule mining, Web page classification, and general statistics such as amount of time spent on a page. In this paper we will focus on mining the different segments content of Web log data entries in order to discover the hidden information and interesting browsing contents from it, then applying clustering algorithm to find similar groups of Web sites that have common browsing contents.
关键词：Web Mining; Web Usage Mining; Log File Analysis; Clustering; K-means; System Monitoring.
