Structured context prediction: A generic approach

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Abstract

Context-aware applications and middleware platforms are evolving into major driving factors for pervasive systems. The ability to also make accurate assumptions about future contexts further enables such systems to proactively adapt to upcoming situations. However, the provision of a reusable system component to facilitate the development of such future-context-aware applications is still challenging - as it requires to be generic but, at the same time, as efficient and accurate as possible. To address these requirements, this paper presents the approach of Structured Context Prediction which constitutes a framework to facilitate the application of existing prediction methods. It allows application developers to integrate domain-specific knowledge by creating a customized prediction model at design time and to select, implement and combine prediction methods for the intended purpose. Feasibility is evaluated by applying a prototype system component to two mobile application scenarios, showing that both high accuracy and efficiency are possible. © 2010 Springer-Verlag Berlin Heidelberg.

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APA

Meiners, M., Zaplata, S., & Lamersdorf, W. (2010). Structured context prediction: A generic approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6115 LNCS, pp. 84–97). Springer Verlag. https://doi.org/10.1007/978-3-642-13645-0_7

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