Fourth International Conference on Hybrid Intelligent Systems (HIS'04) Website Visitor Classification Using Machine Learning Kitakyushu, Japan December 05-December 08 ISBN: 0-7695-2291-2
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICHIS.2004.93
Classifying website 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 website using a minimal amount of information and without a unique identifier. We are able to group visitors into groups without extended user tracking.
Citation:
P. Defibaugh-Chavez, S. Mukkamala, A. H. Sung, "Website Visitor Classification Using Machine Learning," his, pp.384-389, Fourth International Conference on Hybrid Intelligent Systems (HIS'04), 2004 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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