Modeling Uncertainty in Semantic Web Taxonomies Information retrieval systems have to deal with uncertain knowledge and query results should reflect this uncertainty in some manner. 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.
2006-12-06
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