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Published in Rahimi, S., Gandy, L., & Gupta, B. (2006). Extracting Web user profiles using a modified CARD algorithm. 2006 IEEE International Conference on Fuzzy Systems, 582-589. doi: http://dx.doi.org/10.1109/FUZZY.2006.1681770 ©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Abstract

Clustering algorithms are widely used methods for organizing data into useful information. The Competitive Agglomeration for Relational Data (CARD) Algorithm is one such clustering algorithm that is designed to organize user sessions into profiles, where each profile would highlight a particular type of user. The CARD algorithm is a viable candidate for web clustering; however, it does have limitations such as an extended execution time. In addition, the methods that prepare the input data for the CARD algorithm’s use employs concepts which seem to be incomplete. These limitations of the CARD algorithm are explored and modifications are introduced to yield a more practical and efficient algorithm.

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