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.