Semantic Web Mining for Personalization and Recommendation

Abstract

The continuous growth in the size and use of the World Wide Web imposes new methods of design and development of online information services. Most Web structures are large and complicated and users often miss the goal of their inquiry, or receive ambiguous results when they try to navigate through them. On the other hand, the e-business sector is rapidly evolving and the need for Web marketplaces that anticipate the needs of the customers is more evident than ever. Therefore, the requirement for predicting user needs in order to improve the usability and user retention of a Web site can be addressed by personalizing it. Web personalization is defined as any action that adapts the information or services provided by a Web site to the needs of a particular user or a set of users, taking advantage of the knowledge gained from the users’ navigational behavior and individual interests, in combination with the content and the structure of the Web site. The objective of a Web personalization system is to provide users with the information they want or need, without expecting from them to ask for it explicitly.

The aim is to address Web usage mining for Web personalization & recommendation by using semantic analysis & web ontology. Two different approaches for applying ontology have been discussed. Major challenges involved in the implementations and possible solutions are listed. Also future extension by considering other development in data mining has been discussed.