Learning in Fuzzy Description Logics
From International Center for Computational Logic
Learning in Fuzzy Description Logics
Talk by Francesca Alessandra Lisi
- Location: APB 0005
- Start: 13. May 2015 at 10:00 am
- End: 13. May 2015 at 11:30 am
- Research group: Computational Logic
- iCal
Incompleteness and vagueness are inherent properties of knowledge in several real-world domains and are particularly pervading in those domains where entities could be better described in natural language. The issues raised by incomplete and vague knowledge have been traditionally addressed in the field of Knowledge Representation within the stream of research devoted to fuzzy Description Logics (DLs). However, the problem of automatically managing the evolution of fuzzy DL ontologies still remains relatively unaddressed. In this talk, I present a method for inducing fuzzy GCI axioms from any crisp DL knowledge base. The method has been implemented and applied on real-world data in the tourism domain.
