Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling

서지정보

· 발행기관 : 한국지능시스템학회
· 수록지 정보 : International Journal of Fuzzy Logic and Intelligent systems / 8권 / 4호 / 254 ~ 259페이지
· 저자명 : 고광은, 심귀보

초록

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context
awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the
accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context
reasoning method based on Bayesian Network. Our context aware processing is divided into two parts: context modeling and context
reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and
reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be
used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve
the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

참고자료

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