TY - GEN
T1 - Reasoning with the fuzzy description logic f-SHIN
T2 - Theory, practice and applications
AU - Stoilos, Giorgos
AU - Stamou, Giorgos
AU - Pan, Jeff Z.
AU - Simou, Nick
AU - Tzouvaras, Vassilis
N1 - The work of Giorgos Stoilos, Giorgos Stamou, Vassilis Tzouvaras and Nick Simou was partially supported by EU projects X-Media (FP6-26978) and BOEMIE (FP6-027538). We would also like to thank Thanos Athanasiadis for providing the image and segmentation figures.
PY - 2008/12/1
Y1 - 2008/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=58449115485&partnerID=8YFLogxK
UR - http://www.image.ece.ntua.gr/papers/572.pdf
U2 - 10.1007/978-3-540-89765-1-16
DO - 10.1007/978-3-540-89765-1-16
M3 - Published conference contribution
AN - SCOPUS:58449115485
SN - 354089764X
SN - 9783540897644
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 262
EP - 281
BT - Uncertainty Reasoning for the Semantic Web I - ISWC International Workshops, URSW 2005-2007, Revised Selected and Invited Papers
ER -