Representation of Context-Dependent Relevance Relations with Fuzzy Ontologies

Information overload is a common problem in current Information and Knowledge Based Systems. The Web, being the largest public available information source, is particularly affected by this issue, so several approaches to deal with it are being developed by Semantic Web researchers. Most of them are based on using context knowledge to delimit which information is significant to a user, such as the CDR ontology design pattern, our previous contribution to handle relevance depending on context in OWL ontologies. In this work, we extend this proposal with fuzzy Description Logics formalisms in order to represent vague knowledge about context and application-specific facts, and to manage the degree of importance of a relevance relation. A main advantage of our proposal is that current (non-fuzzy) standards and inference engines can be used.