Flexible queries on relational databases using fuzzy logic and ontologies

• Combines fuzzy logic and semantic techniques to perform flexible queries in a relational database.
• Alternative method to fuzzy logic, to execute flexible queries on non-scalar attributes.
• Answers are ordered according with the accomplishment degree to the query.
• Ontologies are used as an attribute domain frame to return semantically similar information to the query.
• Fuzzy logic are used on scalar attributes.

Nowadays there are many proposals that allow users to perform fuzzy queries on relational databases. Regardless of these proposals, fuzzy queries are really useful on scalar values where fuzzy sets can be adjusted to the user needs and domains, but non-scalar values are a more complex task. Here, we extend non-scalar attribute management in fuzzy queries with the use of ontologies. Thus, we allow to compute this kind of queries not only with the similarity relationships defined explicitly on a fuzzy set but with semantically interrelated terms modeled as a domain ontology as well. Moreover, we present the architecture of a novel system that combines both techniques to return an answer as much complete as possible and ordered by a degree of accomplishment. Finally, a qualitative and quantitative study about the use of flexible queries on relational databases is included in this work, as well.