Machine Learning for Better Web Browsing

Adaptive User Interfaces

Volume

Papers from the 2000 AAAI Spring Symposium

Contents

This paper describes a way to help the user browsing the Web using Machine Learning techniques. Two machine learning algorithms, Naive Bayes and k-Nearest Neighbor, are compared on two approaches that differ in the information included in the training examples. Experiments on real-world data confirm that the proposed approaches are promising.