Web site visitor classiflcation using machine learning

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.