Comprehensive Survey of Framework for Web Personalization using Web Mining

ABSTRACT World Wide Web is a global village and a rich source of information. The number of users accessing web sites is increasing day by day. For effective and efficient handling, web mining coupled with recommendation techniques provides personalized contents at the disposal of users. Web Mining is an area of Data Mining dealing with the extraction of interesting knowledge from the World Wide Web. While surfing the web sites, users‟ interactions with web sites are recorded in web usage file. These Web Logs when mined properly are rich source for Web Personalization. Mining of these Web Logs is referred to as Web Usage Mining. This paper presents a comprehensive survey of over 100 research papers dealing with Web Mining framework. General Terms Data Mining, Framework. Keywords Web Mining, Web Log Mining, Web Personalization. 1. INTRODUCTION The expansion of the World Wide Web has resulted in a large amount of data that is now in general freely available for user access. The different types of data have to be managed and organized such that they can be accessed by different users efficiently [Han and Kamber (2001)]. Therefore, the application of data mining techniques on the Web is now the focus of an increasing number of researchers. Several data mining methods are used to discover the hidden information in the Web. However, Web mining does not only mean applying data mining techniques to the data stored in the Web. The algorithms have to be modified such that they better suit the demands of the Web. In accordance with [Kosala