Fluid concepts and creative analogies: computer models of the fundamental mechanisms of thought
Fluid concepts and creative analogies: computer models of the fundamental mechanisms of thought
Uncertainty-Based Information: Elements of Generalized Information Theory
Uncertainty-Based Information: Elements of Generalized Information Theory
Probabilistic Reasoning in Multi-Agent Systems: A Graphical Models Approach
Probabilistic Reasoning in Multi-Agent Systems: A Graphical Models Approach
P-SHOQ(D): A Probabilistic Extension of SHOQ(D) for Probabilistic Ontologies in the Semantic Web
JELIA '02 Proceedings of the European Conference on Logics in Artificial Intelligence
Web-scale information extraction in knowitall: (preliminary results)
Proceedings of the 13th international conference on World Wide Web
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
A method for modeling uncertainty in semantic web taxonomies
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
A report of recent progress in transformation-based error-driven learning
HLT '94 Proceedings of the workshop on Human Language Technology
Ontology acquisition for automatic building of scientific portals
SOFSEM'06 Proceedings of the 32nd conference on Current Trends in Theory and Practice of Computer Science
Computing a transitive opening of a reflexive and symmetric fuzzy relation
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Discovering Groups of Sibling Terms from Web Documents with XTREEM-SG
Journal on Data Semantics XI
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The significance of uncertainty representation has become obvious in the Semantic Web community recently. This paper presents our research on uncertainty handling in automatically created ontologies. A new framework for uncertain information processing is proposed. The research is related to OLE (Ontology LEarning) — a project aimed at bottom–up generation and merging of domain–specific ontologies. Formal systems that underlie the uncertainty representation are briefly introduced. We discuss the universal internal format of uncertain conceptual structures in OLE then and offer a utilisation example then. The proposed format serves as a basis for empirical improvement of initial knowledge acquisition methods as well as for general explicit inference tasks.