情境感知智能家居中的链式案例推理

Tam V. Nguyen, Yi Chang Woo, Deokjai Choi
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引用次数: 9

摘要

在智能家居等普适计算环境中,上下文感知是提供自动化服务的重要组成部分。本文提出了链式基于案例推理(CCBR)作为推理方法,解决了传统基于案例推理(CBR)方法的模糊性,即“在智能家居环境中,在有多个解决方案的特定情况下,我们不知道选择哪个解决方案或活动来满足用户的需求”。本文对智能家居的语境内容进行了阐述。介绍了基于CCBR的上下文感知框架,详细讨论了案例表示、案例适应和相似度计算。我们提出的CCBR集成到虚拟智能家居环境中,获取有关记录的用户操作的知识,以确定他们的偏好,然后同时使用预定义设置激活设备。
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CCBR: Chaining Case Based Reasoning in Context-Aware Smart Home
In ubiquitous computing environments like smart home, context awareness is a very important component which aims at providing automatic services. This paper proposes chaining case based reasoning (CCBR) as the reasoning method which solves the vagueness of traditional case based reasoning (CBR) approach "In the certain case with more than one solution, we don’t know which solution or activity will be chosen to satisfy user's needs in smart home’s context". The context's contents in smart home are described in this paper. Also, we introduce the framework of context awareness based on CCBR, and discuss the case representation, case adaptation, and similarity computation in detail. Our proposed CCBR integrated into the virtual smart home environment acquires knowledge about user actions that are recorded to determine their preferences and then simultaneously activates the devices with predefined settings.
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