Motivations of Extensive Incorporation of Uncertainty in OLE Ontologies

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Authors	NOVÁČEK Vít
Year of publication	2006
Type	Article in Proceedings
Conference	SOFSEM 2006: Theory and Practice of Computer Science: 32nd Conference on Current Trends in Theory and Practice of Computer Science. Student Research Forum Proceedings
MU Faculty or unit	Faculty of Informatics
Citation
Web	http://nlp.fi.muni.cz/projects/ole/pubs.html
Field	Informatics
Keywords	artificial intelligence; semantic web; ontology learning; uncertainty representation; fuzzy sets
Description	Recently, the significance of uncertain information representation has become obvious in the Semantic Web community. This paper presents an ongoing research of uncertainty handling in automatically created ontologies. Proposal of a specific framework is provided. The research is related to OLE (Ontology LEarning), a project aimed at bottom-up generation a nd merging of domain specific ontologies. Formal systems that underlie the uncertai nty representation are briefly introduced. We will discuss a universal internal form at of uncertain conceptual structures in OLE then. The proposed format serves as a basis for inference tasks performed among an ontology. These topics are outlined as motivations of our future work.
Related projects:	Intelligent Models, Algorithms, Methods and Tools for the Semantic Web (realization)