基于不确定事件的自我中心上下文感知模型

M. Caporuscio, P. Inverardi
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引用次数: 3

摘要

平静科技的特点是那些在我们注意力的中心和边缘之间来回移动的技术。也就是说,当中心表示你目前关注的东西时,外围表示你在没有明确关注它的情况下被调谐的东西。上下文感知计算利用了这样一个概念,允许应用程序根据环境(即外围)中感知到的上下文调整其行为(即中心)。在这种设置下的应用程序应该有最少的假设,以便在能够动态适应和学习周围上下文提供的内容的同时进行操作。在本文中,我们讨论了正在进行的设计基于事件的模型的工作,该模型允许应用程序以自我为中心感知外围并评估其相对于应用程序注意力中心的相关性和不确定性。我们特别讨论了我们在设计和开发回声方面正在进行的工作,回声是一种用于自我中心计算的不确定事件模型。回声的特点是:(a)与事件通知模型中实现的通常的联合模式匹配算法不同,(b)通过使用模糊逻辑公式定义的复杂过滤器实现事件关联。本文介绍了回声的规范以及作为SIENA发布/订阅中间件的修改实现而开发的早期原型的设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uncertain event-based model for egocentric context sensing
Calm Technology characterizes those technologies that move forth and back between the center and periphery of our attention. That is, while center denotes what one is currently focused on, periphery denotes what one is attuned to without focusing on it explicitly. Context-aware computing exploits such a concept by allowing applications to adapt their behavior (i.e. the center) in response to the context sensed within the environment (i.e. the periphery). An application in this setting should have minimal assumptions in order to operate while being able to dynamically adapt to and learn what the surrounding context offers.In this paper we discuss ongoing work in designing an event-based model that allows applications to egocentrically perceive the periphery and evaluate its relevance and uncertainty with respect to the center of the application attention. In particular we discuss our ongoing work in designing and developing ECHOES, an uncertain event-model for Egocentric computing. Characteristics of ECHOES are (a) departing from usual conjunctive pattern-matching algorithms implemented in event-notification models and, (b) achieving event correlation through the use of complex filters defined by means of Fuzzy Logic formulas. The paper introduces the specification of ECHOES as well as the design of an early prototype developed as a modified implementation of the SIENA Publish/Subscribe Middleware.
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