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Multidimensional Design of OLAP System for Context-Aware Analysis in the Ambient Intelligence Environment

机译:环境情报环境中的OLAP系统OLAP系统的多维设计

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Ambient Intelligence (AmI) is currently a perspective area of development intelligent systems that react on human presence, their behavior and AmI adapts to requirements based on contextual knowledge. The important issue in the study of AmI is thinking about context-aware preference. In the context of ubiquitous computing technologies there is not any access for users to the system at one point, but in different contexts. This creates need for context-sensitive preferences. The aim of context reasoning is getting new knowledge, so that systems or services were more intelligent. This process is not a trivial problem, so that we propose multidimensional view on context-aware knowledge for support of contextual reasoning. In this paper we introduce a new TCAP procedure for transformation context-aware preference through OLAP in the AmI. The OLAP technology enables us better analyzing contextual dependence on preferences and choosing relevant content for users in the AmI environment.
机译:环境智能(AMI)目前是开发智能系统的透视区域,对人类存在反应,其行为和AMI适应基于语境知识的要求。 AMI研究中的重要问题正在考虑上下文感知偏好。 在普遍存在的计算技术的背景下,没有任何访问用户在一个点到系统的访问,而是在不同的上下文中。 这会为上下文敏感的偏好创造。 上下文推理的目的是获得新的知识,以便系统或服务更聪明。 这个过程不是一个微不足道的问题,因此我们提出了关于支持上下文推理的背景知识的多维观点。 在本文中,我们将通过在AMI中通过OLAP介绍一个新的TCAP过程,用于转换上下文感知首选项。 OLAP技术使我们能够更好地分析对偏好的上下文依赖,并为AMI环境中的用户选择相关内容。

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