Affiliations: Department of Computer Science, University of Haifa,
Haifa, Israel. E-mail: {manevitz, yousef}@cs.haifa.ac.il | Institute of Mathematics and Department of
Experimental Psychology, Oxford, UK
Abstract: An adaptive system designed to assist in navigating the Web is
presented. The core of the system is a user model constructed unobtrusively by
observing the user activity and using only positive information to train
a certain kind of neural network. The system is built upon neural network
techniques designed to attack the problem of user modeling using only positive
examples. The system is composed of three main agents: LEARN, CLASSIFY and
SHADOW which interact around the neural network model to (respectively) build
the user model, apply the user model, and to gather information to train the
user model. LEARN has been extensively tested off-WEB on the Reuters data
base for information retrieval. CLASSIFY has been used to automatically
annotate a WEB-browser with recommendations.