Intelligent context-awareness system using improved self-adaptive back propagation algorithm

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Abstract

Since the context plays a significant role in ubiquitous computing environment, many researches have studied about context-awareness system to improve the performance. An efficient learning mechanism is in importance of context-aware system, but there are seldom algorithms focused on convenience of systems by elaborating the learning mechanism with user's context information. As one of the most adaptable algorithm, Back Propagation provides us favorable inference capability. In this paper, we concentrate on improving the predict ability and reducing the system workload by proposing improved selfadaptive back propagation algorithm. The middleware we proposed improves the predicate capability. Thus, the overall performance becomes better than other systems. By adding system cache to middleware, it is possible for the context-aware system to act faster and improve the workload efficiency. Experiments show that there is an obvious improvement in overall performance of the context-awareness systems. © IFIP International Federation for Information Processing 2007.

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APA

Eo, S. H., Zha, W., You, B. S., Lee, D. W., & Bae, H. Y. (2007). Intelligent context-awareness system using improved self-adaptive back propagation algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4761 LNCS, pp. 329–338). Springer Verlag. https://doi.org/10.1007/978-3-540-75664-4_33

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