2001 ReasWithinFuzzyDescLog

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Subject Headings Relational learning, probabilistic relational models, knowledge discovery, graphical models, dependency networks, pseudolikelihood estimation.

Notes

Cited By

~364 http://scholar.google.com/scholar?cites=5475226430251691620

Quotes

Abstract

  • Description Logics (DLs) are suitable, well-known, logics for managing structured knowledge. They allow reasoning about individuals and well de¯ned concepts, i.e. set of individuals with common properties. The experience in using DLs in applications has shown that in many cases we would like to extend their capabilities. In particular, their use in the context of Multimedia Information Retrieval (MIR) leads to the convincement that such DLs should allow the treatment of the inherent imprecision in multimedia object content representation and retrieval. In this paper we will present a fuzzy extension of ALC, combining Zadeh's fuzzy logic with a classical DL. In particular, concepts becomes fuzzy and, thus, reasoning about imprecise concepts is supported. We will define its syntax, its semantics, describe its properties and present a constraint propagation calculus for reasoning in it.


References


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2001 ReasWithinFuzzyDescLogUmberto StracciaReasoning within Fuzzy Description LogicsJAIR Journal Serieshttp://www.cs.cmu.edu/afs/cs.cmu.edu/project/jair/OldFiles/OldFiles/pub/volume14/straccia01a.pdf2001