Web Log Mining using Improved Version of Proposed Algorithm

A Technique for Improving Web Mining using Enhanced Genetic Algorithm

World Wide Web is growing at a very fast pace and makes a lot of information available to the public. Search engines used conventional methods to retrieve information on the Web; however, the search results of these engines are still able to be refined and their accuracy is not high enough. One of the methods for web mining is evolutionary algorithms which search according to the user interests...

Web Log Mining using Improved Version of Apriori Algorithm

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...

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...

Optimizing Membership Functions using Learning Automata for Fuzzy Association Rule Mining

The Transactions in web data often consist of quantitative data, suggesting that fuzzy set theory can be used to represent such data. The time spent by users on each web page is one type of web data, was regarded as a trapezoidal membership function (TMF) and can be used to evaluate user browsing behavior. The quality of mining fuzzy association rules depends on membership functions and since t...