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The Scientific World Journal
Volume 2015 (2015), Article ID 193631, 16 pages
http://dx.doi.org/10.1155/2015/193631
Research Article

A Dynamic Recommender System for Improved Web Usage Mining and CRM Using Swarm Intelligence

Department of Computer Science and Engineering, SRM University, Chennai 603203, India

Received 6 March 2015; Revised 13 April 2015; Accepted 15 April 2015

Academic Editor: Rafael Valencia-García

Copyright © 2015 Anna Alphy and S. Prabakaran. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In modern days, to enrich e-business, the websites are personalized for each user by understanding their interests and behavior. The main challenges of online usage data are information overload and their dynamic nature. In this paper, to address these issues, a WebBluegillRecom-annealing dynamic recommender system that uses web usage mining techniques in tandem with software agents developed for providing dynamic recommendations to users that can be used for customizing a website is proposed. The proposed WebBluegillRecom-annealing dynamic recommender uses swarm intelligence from the foraging behavior of a bluegill fish. It overcomes the information overload by handling dynamic behaviors of users. Our dynamic recommender system was compared against traditional collaborative filtering systems. The results show that the proposed system has higher precision, coverage, measure, and scalability than the traditional collaborative filtering systems. Moreover, the recommendations given by our system overcome the overspecialization problem by including variety in recommendations.