Novel Hybrid k-D-Apriori Algorithm for Web Usage Mining

An efficient algorithm for Web usage mining

With the growing popularity of the World Wide Web (Web), large volumes of data are gathered automatically by Web servers and collected in access log files. Analysis of server access data can provide significant and useful information. In this paper, we address the problem of Web usage mining, i.e. mining user patterns from one or more Web servers for finding relationships between data stored [C...

A Hybrid Approach to Web Usage Mining

With the large number of companies using the Internet to distribute and collect information, knowledge discovery on the web, or web mining, has become an important research area. Web usage mining, which is the main topic of this paper, focuses on knowledge discovery from the clicks in the web log for a given site (the so-called click-stream), especially on analysis of sequences of clicks. Exist...

Web Log Mining using Improved Version of Apriori Algorithm

Mining of Web Server Logs using Extended Apriori Algorithm

Association rule mining is one of the most significant techniques in the field of data mining. It is very useful in discovering relationships hidden in large transaction datasets such as frequent patterns, associations etc. One of the popular and important algorithms in this category is Apriori algorithm which finds frequent itemsets using an iterative approach. But it suffers from a major limi...

Web Log Mining using Improved Version of Apriori Algorithm

Association Rule mining is one of the important and most popular data mining technique. It extracts interesting correlations, frequent patterns and associations among sets of items in the transaction databases or other data repositories. Most of the existing algorithms require multiple passes over the database for discovering frequent patterns resulting in a large number of disk reads and placi...