Valentin's Blog

The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. Recently, different applications based on this vision have been designed, e.g. in the fields of knowledge management, community web portals, e-learning, multimedia retrieval, etc. It is obvious that the complex metadata descriptions generated on the basis of pre-defined ontologies serve as perfect input data for machine learning techniques. In this paper we propose an approach for clustering ontology-based metadata. Main contributions of this paper are the definition of a set of similarity measures for comparing ontology-based metadata and an application study using these measures within a hierarchical clustering algorithm.

A. Mädche and Valentin Zacharuas, Proceedings of the Joint Conferences 13th European Conference on Machine Learning (ECML'02) and 6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'02).

Entire Paper is here.

(older paper, just posted it for completeness)

Labels: publication, SemanticWeb