DocumentCode
3369929
Title
Fuzzy D-S Theory Based Fuzzy Ontology Context Modeling and Similarity Based Reasoning
Author
Huanyu Zhou ; Yongheng Wang ; Kening Cao
Author_Institution
Coll. of Inf. Sci. & Eng., Hunan Univ., Changsha, China
fYear
2013
fDate
14-15 Dec. 2013
Firstpage
707
Lastpage
711
Abstract
The data that the Internet of Things(IOT) produced is fuzzy and enormous, and the Complex Events Processing(CEP) which is the key part of the Internet of Things need to meet the big data´s quantity and complexity. In CEP, how to describe the context and infer from the context is the most important, and in this paper, a fuzzy D-S theory and fuzzy ontology based context model is proposed, according to the model, we design a similarity based context reasoning method. The experimental results show that this method can support fuzzy context in CEP and have better performance and accuracy than other methods.
Keywords
fuzzy reasoning; fuzzy set theory; ontologies (artificial intelligence); CEP; IOT; Internet of Things; big data complexity; big data quantity; complex events processing; fuzzy D-S theory; fuzzy ontology context modeling; similarity based context reasoning method; Cognition; Computational modeling; Context; Context modeling; Object oriented modeling; Ontologies; Vehicles; CEP; D-S Theory; IOT; context modeling; context reasoning;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security (CIS), 2013 9th International Conference on
Conference_Location
Leshan
Print_ISBN
978-1-4799-2548-3
Type
conf
DOI
10.1109/CIS.2013.154
Filename
6746522
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