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Web site visitor classiflcation using machine learning

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3 Author(s)
Defibaugh-Chavez, P. ; Dept. of Comput. Sci., New Mexico Tech., NM, USA ; Mukkamala, S. ; Sung, A.H.

Classifying Web site visitors allows organizations to present customized content and effectively allocate resources. Traditional methods of visitor classification involve tracking individual users over many sessions via a unique identifier such as the IP address or a cookie. These methods are either too general or strip the visitor of a level of privacy. In this paper we use machine learning techniques to classify visitors of a data-centric Web site using a minimal amount of information and without a unique identifier. We are able to group visitors into groups without extended user tracking.

Published in:

Hybrid Intelligent Systems, 2004. HIS '04. Fourth International Conference on

Date of Conference:

5-8 Dec. 2004