Silvia Calegari

Learn More
This paper shows how a Fuzzy Ontology based approach can improve semantic documents retrieval. After formally defining a Fuzzy Knowledge Base, it is discussed a special type of new non-taxonomic fuzzy relationships, called (semantic) correlations. These correlations, first assigned by experts, are updated after querying, or when a document has been inserted(More)
Ontologies have proved to be very useful in sharing concepts across applications in an unambiguous way. Nowadays, in ontology-based applications information is often vague and imprecise. This is a well-known problem especially for semantics-based applications, such as e-commerce, knowledge management, web portals, etc. In computer-aided reasoning, the(More)
An algorithm for the automatic labeling of topics accordingly to a hierarchy is presented. Its main ingredients are a set of similarity measures and a set of topic labeling rules. The labeling rules are specifically designed to find the most agreed labels between the given topic and the hierarchy. The hierarchy is obtained from the Google Directory service,(More)
This paper presents an enrichment of classical computational ontologies with fuzzy logic to create fuzzy ontologies. It is a step towards managing vagueness and facing the nuances of natural languages in ontology-based applications. Our proposal is implemented in the KAON ontology editor, that allows to handle ontology concepts in a high-level environment.