Datil: Learning Fuzzy Ontology Datatypes

Proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, (IPMU-18), Communications in Computer and Information Science, Volume 854, Springer, pages 100--112, 2018.


Abstract:
Real-world applications using fuzzy ontologies are increasing in the last years, but the problem of fuzzy ontology learning has not received a lot of attention. While most of the previous approaches focus on the problem of learning fuzzy subclass axioms, we focus on learning fuzzy datatypes. In particular, we describe the Datil system, an implementation using unsupervised clustering algorithms to automatically obtain fuzzy datatypes from different input formats. We also illustrate the practical usefulness with an application: semantic lifestyle profiling.