A Web surfer model incorporating topic continuity Sankar K. Pal, B. Lakshmi Narayanan, and Soumitra Dutta   View Paper (PDF)   Return to May 2005, Volume 17, Issue 5 Abstract This paper describes a surfer model which incorporates information about topic continuity derived from the surfer's history. Therefore, unlike earlier models, it captures the interrelationship between categorization (context) and ranking of Web documents simultaneously. The model is mathematically formulated. A scalable and convergent iterative procedure is provided for its implementation. Its different characteristic features, as obtained from the joint probability matrix, and their significance in Web intelligence are mentioned. Experiments performed on Web pages obtained from WebBase confirm the superiority of the model. ©2006 Association for Computing Machinery