摘要
上下文感知系统需要获取和共享多种上下文知识,不仅包含环境参数的具体取值,也包含对环境状态描述时所用的词汇,也就是概念。上下文知识具有与生俱来的动态性,在设计时难以预知系统可能涉及的上下文信息。而大多数已有的系统缺乏完善的动态上下文知识维护机制,因此不支持上下文感知应用的运行时的扩展。提出一个基于本体的层次化上下文模型,以及基于此模型的动态上下文知识获取与共享框架(DCASI)。框架中按需分散获取机制让各类上下文知识出自最有资格定义它的实体,使得上下文知识充足而又不冗余;双库集中共享机制按共享的不同作用维护两个知识库,有效支持了新上下文知识的定义和发现。原型系统验证了本框架的有效性。
Context-aware systems need to acquire and share various kinds of context knowledge,which not only include the concrete values of environmental parameters, but the vocabularies used to describe the environmental states, i. e. , concepts. Context knowledge is inherently dynamic. It is difficult to predict the context information involved in the system at the moment of design. Most of existing systems lack of effective mechanisms for dynamic context knowledge maintenance, thus unable to support run-time scalability of context-aware applications. This paper introduced an ontologybased hierarchical context model. On the basis of this model, a dynamic context knowledge acquisition and sharing infrastructure （DCASI） was proposed. The mechanism of distributed acquisition on demand ensures that each class of context knowledge comes,from the entity with the most competence to define it, which makes the context knowledge in the system sufficient but not redundant. The mechanism of centralized sharing with double-repository maintains two knowledge repositories according to different functions, thereby efficiently supports the definition and discovery of new context knowledge. A prototype system was implemented and the proposed infrastructure was validated.
出处
《计算机科学》
CSCD
北大核心
2009年第9期218-223,共6页
Computer Science
基金
国家自然科学基金项目(60803044)
国家863基金项目(2006AA01Z198)
教育部高等学校博士学科点专项科研基金项目(20070699014)
西北工业大学博士论文创新基金项目(CX200814)资助
