Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
User Modeling and User-Adapted Interaction
Adaptive Assistants for Customized E-Shopping
IEEE Intelligent Systems
Characterizing customer groups for an e-commerce website
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Web usage mining based on probabilistic latent semantic analysis
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Pattern Recognition, Third Edition
Pattern Recognition, Third Edition
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We address the problem of adaptivity of the interaction between an e-shopping application and its users. Our approach is novel, as it is based on the construction of an Artificial Immune Network (AIN) in which a mutation process is incorporated and applied to the customer profile feature vectors. We find that the AIN-based algorithm yields clustering results of users' interests that are qualitatively and quantitatively better than the results achieved by using other more conventional clustering algorithms. This is demonstrated on user data that we collected using Vision.Com, an electronic video store application that we have developed as a test-bed for research purposes.