Paper Details

Web surfing has become a popular activity for many consumers to make purchases online. Consumers alsoseek relevant information on products and services before they commit to buy. Though the World Wide Web is the biggestsource of information and contains a tremendous amount of data, most of the data is irrelevant and inaccurate fromusers’ point of view. Consequently, it has become increasingly necessary for users to utilize automated tools such asrecommender systems in order to discover, extract, filter, and evaluate the desired information and resources. Webrecommender systems predict the information needs of users and provide them with recommendations to facilitate theirnavigation. This paper proposes a Web recommender system. This system constructs a knowledge base using fuzzytemporal Web access patterns as input. Fuzzy logic is applied to requested resources of periodic pattern -based Webaccess activities. The fuzzy representation is used to construct a knowledge base of the user’s Web access habits andbehaviors. The Knowledge base is used to generate association rules which are used to provide timely personalizedrecommendations to the user. Experimental results on the session data of a Web site showed the effectiveness of thisapproach.

Ms. V. T. Chavan, Prof. S. K. Shirgave, “WEB RECOMMENDER SYSTEM BASED ON CONSUMER BEHAVIOR MODELING USING FUZZY REPRESENTATION”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 2, Issue 6, pp. 375-383, June 2015.