Machine learning for better Web browsing
Dunja Mladeni� · 2000
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 realworld data confirm that the proposed approaches are promising.