Extraction of Behavioral Patterns from Pre-processed Web Usage Data for Web Personalization

Data on World Wide Web has been growing in an exponential manner. This raises a severe concern on information overload challenges for the users. Retrieving the most relevant information from the web as per the user requirement has become hard because of the large collection of heterogeneous documents. One approach to overcome this is to personalize the information available on the Web according to user requirements. This is called Web Personalization process that adjusts information/services delivered by a Web to the needs of each user or group of users, taking their behavioral patterns. Frequent Sequential Patterns (FSPs) that are extracted from Web Usage Data (WUD) are very important for analyzing and understanding users' behavior to improve the quality of services offered by the World Wide Web (WWW). User behavioral patterns are required to build profiles of each user, using which Personalization of website is made.