A fuzzy logic-based approach to semantic query answering with missing values

Semantic Query Answering consists of retrieving individuals from a Knowledge Base, usually an OWL 2 ontology or an RDF knowledge graph, that satisfy a Semantic Query expressed via query terms. This paper proposes a novel approach to improve Semantic Query Answering in cases where individuals have missing values with respect to the query terms occurring in a Semantic Query. In our approach, the retrieved instances satisfy some query terms, but not necessarily all. Our general approach, based on the use of fuzzy aggregation operators, is complemented with concrete strategies to evaluate such Semantic Queries, together with an implemented prototype.