Abstract
Context-aware computing is a hot area in ubiquitous computing. There are several challenges to be covered. This paper focuses on context reasoning, which means deducing higher context from raw sensor data. The context reasoning problem is discussed on two different levels: context inference/recognition concerning the generation of context atoms from raw sensor data, and context reasoning concerning the composition of context atoms and deduction of higher-level context. In this paper, we discuss some commonly used reasoning technologies in context-aware systems, including rule-based logics and machine learning methods. Besides, a clustering algorithm, the Symbol Clustering Map, is introduced to learn the current context.
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Jie, S., ZhaoHui, W. (2006). Context Reasoning Technologies in Ubiquitous Computing Environment. In: Sha, E., Han, SK., Xu, CZ., Kim, MH., Yang, L.T., Xiao, B. (eds) Embedded and Ubiquitous Computing. EUC 2006. Lecture Notes in Computer Science, vol 4096. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11802167_103
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DOI: https://doi.org/10.1007/11802167_103
Publisher Name: Springer, Berlin, Heidelberg
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