Modeling Web Navigation Using Grammatical Inference

In this paper, a method that models user navigation on the Web, as opposed to a single Web site, is presented, aiming to assist the user by recommending pages. User modeling is done through data mining of Web usage logs, resulting in aggregate, rather than personal models. The proposed approach extends Grammatical Inference methods, by introducing an extra merging criterion, which examines the semantic similarity of automaton states. The experimental results showed that the method does indeed facilitate the modeling of Web navigation, which was not possible with the existing Web usage mining methods. However, a content-based recommendation model is shown to still outperform the proposed method, which suggests that the knowledge of ∗Running head: Modeling Web Navigation using G.I. †Contact: Georgios Paliouras, Institute of Informatics and Telecommunications, NCSR “Demokritos”, P.O. BOX 60228, Ag. Paraskevi 15310, Athens, Greece, Tel: +3