Prediction of Web Usages Using Apriori Algorithm

Abstract

Web mining has become a necessity to use efficient information retrieval techniques to find and order the desired information. Although there exists quite some confusion about the Web mining, the most recognized approach is to categorize Web mining into three areas: Web content mining, Web structure mining, and Web usage mining. Web usage mining is one of the most popular web mining techniques in order to generate the web usage patterns which can be further exploited in better personalization, improving navigations, recommendations, and recognition of web sites and attracting more advertisements etc. Web Usage Mining is a great research area in discovering the interested patterns of user’s usage data on the web. It focuses on the techniques that could predict user behavior while the user interacts with Web. Frequent pattern mining is an important knowledge discovery technique in data mining. Most frequent pattern mining has been designed with the traditional support-confidence framework that generates more interesting kinds of patterns. This system predicts the web usage using the Apriori algorithm which is also discovered the frequent patterns with support measure. In this system, Apriori algorithm is applied on NASA web log data in order to predict the usage patterns. This system accepts the NASA web log and preprocesses these data to improve data quality and produce the usages patterns. Finally, this system assesses the performance of Apriori algorithm. The approach used in this system, helps the website designers to improve their website usability.