Reasoning with the fuzzy description logic f-SHIN: Theory, practice and applications

Stoilos, G; Stamou, G; Pan, JZ; Simou, N; Tzouvaras, V

dc.contributor.author	Stoilos, G	en
dc.contributor.author	Stamou, G	en
dc.contributor.author	Pan, JZ	en
dc.contributor.author	Simou, N	en
dc.contributor.author	Tzouvaras, V	en
dc.date.accessioned	2014-03-01T02:45:46Z
dc.date.available	2014-03-01T02:45:46Z
dc.date.issued	2008	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32376
dc.subject	Fuzzy Description Logic	en
dc.subject.other	Description logic (DL)	en
dc.subject.other	Description Logics (DL)	en
dc.subject.other	Ontology languages	en
dc.subject.other	Reasoning algorithms	en
dc.subject.other	Reasoning systems	en
dc.subject.other	Semantic Web (SWeb)	en
dc.subject.other	Use cases	en
dc.subject.other	Data description	en
dc.subject.other	Inference engines	en
dc.subject.other	Information theory	en
dc.subject.other	Ontology	en
dc.subject.other	Programming theory	en
dc.subject.other	Semantic Web	en
dc.subject.other	Semantics	en
dc.subject.other	Fuzzy inference	en
dc.title	Reasoning with the fuzzy description logic f-SHIN: Theory, practice and applications	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-540-89765-1-16	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-540-89765-1-16	en
heal.publicationDate	2008	en
heal.abstract	The last couple of years it is widely acknowledged that uncertainty and fuzzy extensions to ontology languages, like Description Logics (DLs) and OWL, could play a significant role in the improvement of many Semantic Web (SW) applications. Many of the tasks of SW like trust, matching, merging, ranking usually involve confidence or truth degrees that one requires to represent and reason about. Fuzzy DLs are able to represent vague concepts such as a ""Tall"" person, a ""Hot"" place, a ""MiddleAged"" person, a ""near"" destination and many more. In the current paper we present a fuzzy extension to the DL SHIN. First, we present the semantics while latter a detailed reasoning algorithm that decides most of the key inference tasks of fuzzy-SHIN. Finally, we briefly present the fuzzy reasoning system FiRE, which implements the proposed algorithm and two use case scenarios where we have applied fuzzy DLs through FiRE. © 2008 Springer Berlin Heidelberg.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-540-89765-1-16	en
dc.identifier.volume	5327 LNAI	en
dc.identifier.spage	262	en
dc.identifier.epage	281	en