Application of Web Mining Using Clonal Selection Algorithm

Abstract

 Abstract—The Clonal Selection Algorithm is one of the most important algorithms of Artificial Immune Systems. In addition, it is has taken place in multiple studies in recent years. In this study, most visited web pages have been identified from internet access file by using a Clonal Selection Algorithm. In here, Clonal Selection Algorithm is applied to web mining association analysis. Necessary changes according to the association rules have been made in selection and mutation mechanisms of the Clonal Selection Algorithm. Results showed that the proposed method can be applied successfully for association rules. Web mining is the detection and analysis of information needed from internet records and web files by using some data obtaining techniques. In this study, the Clonal Selection Algorithm (CSA) has been used in web mining. Necessary changes have been made in selection and mutation mechanisms of the CSA. These changes were made appropriate according to the web mining. Logical patterns obtained from web records and the most visited web pages were determined. The determination procedure was carried out as quickly as possible. Many studies about extraction of meaningful patterns from web data have been carried out up to now. These studies have subjected web content mining, web structure mining and web usage mining which are types of web mining. Artificial intelligence techniques are used quite a lot in this area. Some studies in the field of web mining are given below. Many studies have been conducted so far on web mining. Some of these studies are as follow. Agrawal et al. have proposed and used the mathematical model of association rule (1). Srivastava et al., in their studies indicated the basic concepts and general information about web usage mining. Intent of their study is to gather information about the difficulties encountered on web usage mining and provides recommendations for overcoming these challenges (2). Uguz et al., achieve meaningful information from user access records by applying Apriori algorithm on users' web data records in their studies (3). Gao has stated that data mining about association rule occurs in two phases, finding all frequently passing items and production of strong association rules from these passing frequently items. Apriori algorithm