Using machine learning techniques for automatic evaluation of Web sites

Abstract

We present an intelligent search tool which we developed in order to automate search and evaluation of Web sites. We used TFIDF heuristics to determine term frequency and decision trees to evaluate the quality of sites. Training set for the decision tree contained manually evaluated Web sites. Each Web site was described by the combination of various attributes, complexity metrics and the evaluation. The intelligent search tool is equipped with a user-friendly interface, which enables people to exploit the tool to its limits with minimum effort. For testing purposes, we looked for sites with different content. The set of sites which was the result of using the intelligent search tool has been evaluated by a group of students.