Models for User Access Patterns on the Web: Semantic Content versus Access History

This work focuses on clustering a site into groups of documents that are predictive of future user accesses. Two approaches have been developed and tested. The first approach uses semantic information inherent in the documents to facilitate the clustering process. User access history is then used to reorganize the clusters iteratively so as to better indicate access patterns. This method was found to not be an effective solution to the problem. Hence, a second method based on hierarchical clustering of trail information was developed. This method is shown to be far more effective than the first method.