Modeling Degrees of Conceptual Overlap in Semantic Web Ontologies

Information retrieval systems have to deal with uncertain knowledge and query results should reflect this uncertainty in some manner. However, Semantic Web ontologies are based on crisp logic and do not provide well-defined means for expressing uncertainty. We present a new probabilistic method to approach the problem. In our method, degrees of subsumption, i.e., overlap between concepts can be modeled and computed efficiently using Bayesian networks based on RDF(S) ontologies. Degrees of overlap indicate how well an individual data item matches the query concept, which can be used as a well-defined measure of relevance in information retrieval tasks. 1 Ontologies and Information Retrieval A key reason for using ontologies in information retrieval systems, is that they enable the representation of background knowledge about a domain in a machine understandable format. Humans use background knowledge heavily in information retrieval tasks [7]. For example, if a person is searching f...

• Type: Conference
• Year: 2005
• Where: SEMWEB
• Authors: Markus Holi, Eero Hyvönen
• Keywords: Information Retrieval, Information Retrieval System, Ontologies, SEMWEB 2005