Uncertainty and the Semantic Web

Abstract

The semantic Web must handle information from applications that have special knowledge representation needs and that face uncertain, imprecise knowledge. More precisely, some applications deal with random information and events, others deal with imprecise and fuzzy knowledge, and still others deal with missing or distorted information - resulting in uncertainty. To deal with uncertainty in the semantic Web and its applications, many researchers have proposed extending OWL and the description logic (DL) formalisms with special mathematical frameworks. Researchers have proposed probabilistic, possibilistic, and fuzzy extensions, among others. Researchers have studied fuzzy extensions most extensively, providing impressive results on semantics, reasoning algorithms, and implementations. Building on these results, we've created a fuzzy extension to OWL called Fuzzy OWL. Fuzzy OWL can capture imprecise and vague knowledge. Moreover, our reasoning platform, fuzzy reasoning engine (FiRE), lets Fuzzy OWL capture and reason about such knowledge