Minimalistic fuzzy ontology reasoning: An application to Building Information Modeling

This paper presents a minimalistic reasoning algorithm to solve imprecise instance retrieval in fuzzy ontologies with application to querying Building Information Models (BIMs)-a knowledge representation formalism used in the construction industry. Our proposal is based on a novel lossless reduction of fuzzy to crisp reasoning tasks, which can be processed by any Description Logics reasoner. We implemented the minimalistic reasoning algorithm and performed an empirical evaluation of its performance in several tasks: interoperation with classical reasoners (Hermit and TrOWL), initialization time (comparing TrOWL and a SPARQL engine), and use of different data structures (hash tables, databases, and programming interfaces). We show that our software can efficiently solve very expressive queries not available nowadays in regular or semantic BIMs tools. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

This paper introduces a minimalistic reasoning algorithm for imprecise instance retrieval in fuzzy ontologies, specifically applied to querying Building Information Models (BIMs) in the construction industry. Through empirical evaluation, the algorithm is shown to efficiently solve expressive query tasks.