Access Patterns in Web Log Data: A Review
نویسندگان
چکیده
The traffic on World Wide Web is increasing rapidly and huge amount of information is generated due to users interactions with web sites. To utilize this information, identifying usage pattern of users is very important. Web Usage Mining is the application of data mining techniques to discover the useful, hidden information about the users and interesting patterns from data extracted from Web Log files. It supports to know frequently accessed pages, predict user navigation, improve web site structure etc. In order to apply Web Usage Mining, various steps are performed. This paper discusses the process of Web Usage Mining consisting steps: Data Collection, Pre-processing, Pattern Discovery and Pattern Analysis. It has also presented several approaches such as statistical analysis; clustering, association rules and sequential pattern are being used to discover patterns in web usage mining. The pattern analysis phase means applying data mining techniques such as SQL and OLAP on the pattern discovery data to filter insignificant information to obtain the valuable information.
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