Implementing APRIORI Algorithm on Web serve log
Ankit Kharwar, Viral Kapadia, Nilesh B. Prajapati, Premal C. Patel · 2011
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 behaviour at a Web site. Web server data correspond to the user logs that are collected at Web server. In order to produce the usage patterns and user behaviours, this paper implements the high level process of Web Usage Mining using basic Association Rules algorithm call Apriori Algorithm. Web Usage Mining consists of three main phases, namely Data Pre-processing, Pattern Discovering and Pattern Analysis. Server log files become a set of raw data where it's must go through with all the Web Usage Mining phases to producing the final results. Here, Web Usage Mining, approach has been combining with the basic Association Rules, Apriori Algorithm to optimize the content of the serve log data. Finally, this paper will present a finding association Rule from server log which are useful in many application like cache for web page, Marketing, Targeted Advertising etc.