Selective Markov models for predicting Web page accesses

Mukund Deshpande, George Karypis
2004 ACM Transactions on Internet Technology  
The problem of predicting a user's behavior on a web-site has gained importance due to the rapid growth of the world-wide-web and the need to personalize and influence a user's browsing experience. Markov models and their variations have been found well suited for addressing this problem. Of the different variations or Markov models it is generally found that higher-order Markov models display high predictive accuracies. However higher order models are also extremely complicated due to their
more » ... ge number of states that increases their space and runtime requirements. In this paper we present different techniques for intelligently selecting parts of different order Markov models so that the resulting model has a reduced state complexity and improved prediction accuracy. We have tested our models on various datasets and have found that their performance is consistently superior to that obtained by higher-order Markov models.
doi:10.1145/990301.990304 fatcat:ikn27auq7fhhzbinysor35sevu