Dynamic Prediction of Web Requests
CEC03: 2003 IEEE Congress on Evolutionary Computation, Canberra, Australia, 8th - 12th December 2003, pp. 2034-2041
KEYWORDS:
Genetic Algorithms,
Internet,
Web Intelligence
ABSTRACT
As an increasing number of users access information on the World Wide Web, there is a opportunity to improve well known strategies for web prefetching, dynamic user modeling and dynamic site customization in order to obtain better subjective performance and satisfaction in web surfing. We propose a new method to exploit user navigational path behavior to predict, in real-time, future requests. Real-time user adaptation avoids the use of statistical techniques on web logs by adopting a predictive user model. We designed a new model derived from the Finite State Machine (FSM) formalism together with an evolutionary algorithm that evolves a population of FSMs for achieving a good prediction rate, and we evaluated the performance of the prediction system using the concepts of precision and applicability.
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[BCSq03] D. Bonino, F. Corno, G. Squillero, "Dynamic Prediction of Web Requests," CEC03: 2003 IEEE Congress on Evolutionary Computation, Canberra, Australia, 8th - 12th December 2003, pp. 2034-2041 |
