• 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