Knowledge modelling for deductive web mining

Abstract

Knowledge-intensive methods that can altogether be characterised as deductive web mining (DWM) already act as supporting technology for building the semantic web. Reusable knowledge-level descriptions may further ease the deployment of DWM tools. We developed a multi-dimensional, ontology-based framework, and a collection of problem-solving methods, which enable to characterise DWM applications at an abstract level. We show that the heterogeneity and unboundedness of the web demands for some modifications of the problem-solving method paradigm used in the context of traditional artificial intelligence. © Springer-Verlag Berlin Heidelberg 2004.