Representing uncertainty in RuleML

Damasio, CV; Stoilos, G; Pan, JZ; Straccia, U

dc.contributor.author	Damasio, CV	en
dc.contributor.author	Stoilos, G	en
dc.contributor.author	Pan, JZ	en
dc.contributor.author	Straccia, U	en
dc.date.accessioned	2014-03-01T01:57:35Z
dc.date.available	2014-03-01T01:57:35Z
dc.date.issued	2008	en
dc.identifier.issn	0169-2968	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/28443
dc.subject.classification	Computer Science, Software Engineering	en
dc.subject.classification	Mathematics, Applied	en
dc.subject.other	DEDUCTIVE DATABASES	en
dc.subject.other	POSSIBILISTIC LOGIC	en
dc.subject.other	FUZZY CONSTANTS	en
dc.subject.other	PROGRAMS	en
dc.title	Representing uncertainty in RuleML	en
heal.type	journalArticle	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	The RuleML initiative defines a normalized markup for expressing and exchange rules in the Semantic Web. However, the syntax of the language is still limited and lacks features for representing rule-based languages capable of handling uncertainty and vagueness. It is desirable to have a general extension of RuleML which accommodates major existing languages proposed in the latest two decades. The main contribution of the paper is to propose such a general extension, showing how to encode many of the existing languages in this extension. It is detailed the important case of fuzzy rule languages. We hope this work can also provide some insights on how to cover uncertainty in the RIF framework.	en
heal.publisher	IOS PRESS	en
heal.journalName	FUNDAMENTA INFORMATICAE	en
dc.identifier.isi	ISI:000253199400004	en
dc.identifier.volume	82	en
dc.identifier.issue	3	en
dc.identifier.spage	265	en
dc.identifier.epage	288	en