Semi-automated web resource discovery and analysis : an approach based on interactive machine learning principles

Abstract

This report presents a semi-automated approach to web Resource Discovery based on an architecture in which both human learning and machine learning is integrated in the same model. The fundamental idea of the semi-automated approach is to let the machine automatically identify semantic ambiguities and ask a human analyst to resolve them. An application prototype is developed that demonstrates an experimental Focused Crawler algorithm and the use of the ISO 13250 Topic Map standard for the purpose of knowledge representation. The main area of deployment is for use in Competitive Intelligence activities on the Internet.