Implementation of Web Usage Mining Using APRIORI and FP Growth Algorithms

Web Usage Mining is the application of data mining techniques to discover interesting usage patterns from Web data, in order to understand and better serve the needs of Web-based applications. Usage data captures the identity or origin of Web users along with their browsing behavior at a Web site. Web usage mining itself can be classified further depending on the kind of usage data considered. They are web server data, application server data and application level data. Web server data correspond to the user logs that are collected at Web server. Some of the typical data collected at a Web server include IP addresses, page references, and access time of the users and is the main input to the present Research. This Research work concentrates on web usage mining and in particular focuses on discovering the web usage patterns of websites from the server log files. The comparison of memory usage and time usage is compared using Apriori algorithm and Frequent Pattern Growth algorithm.