Evaluation of term-based queries using possibilistic ontologies
Résumé
In multiple-source information systems, attribute values are often assessed in linguistic terms belonging to different vocabularies. The request itself, which may include preferences, may be expressed using terms of another vocabulary, raising the problem of matching the query and the information in a semantic manner. The fuzzy pattern matching framework allows us to compute matching degrees between queries and data represented by fuzzy sets, even if they do not perfectly match. The qualitative pattern matching no longer requires a fuzzy set representation thanks to the use of ontologies for computing similarity degrees between terms. This allows us to deal with information querying in face of heterogeneous sources of information. This chapter presents this tool and its application to database and textual information retrieval on two examples.