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
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;
Conference_Titel :
Computational Intelligence and Security (CIS), 2013 9th International Conference on
Conference_Location :
Leshan
Print_ISBN :
978-1-4799-2548-3
DOI :
10.1109/CIS.2013.154