Abstract—To be globally competent and competitive a successful presence on the web is necessary to sustain and retain itself in the market. The WWW is an interesting area for data mining because of abundance of information. Web users exhibit a variety of navigational interests through clicking a sequence of web pages. Analysis of this data will lead to discover many interesting patterns and facilitate users to locate more preferable web pages. Advanced mining processes are needed for this knowledge to be extracted, understood and used. Web Usage Mining (WUM) systems are specifically designed to carry out this task by analyzing the data representing usage data about a particular Web Site. The semantic information of the Web page contents is generally not included in Web usage mining. Online recommendation and prediction is one of the web usage mining applications. In this paper we present architecture for integrating semantic information about the products with web log data and generate a list of recommended products by using LCS Algorithm.
Index Terms—WUM, LCS, Semantic Web, RDF, Recommendation.
Sneha Y. S is with the Anna University of Technology, Coimbatore, India and Sr lecturer in Dept of CSE JSSATE, Bangalore, India (e-mail: sneha_girish@yahoo.com).
Dr. G. Mahadevan is with the AMCEC Bangalore, India (e-mail:g_mahadevan@yahoo.com).
[PDF]
Cite: Sneha Y. S, G Mahadevan, and Madhura Prakash, "A Personalized Product Based Recommendation System Using Web Usage Mining and Semantic Web,"
International Journal of Computer Theory and Engineering vol. 4, no. 2, pp. 202-205, 2012.
