Algorithms for Rule Generation and Matchmaking in Context-Aware System

Abstract

针对现有上下文感知系统中的规则主要依靠开发者或用户手工定义的问题,提出了一种基于粗糙集理论的自动规则生成方法.该方法将上下文感知系统视为一种决策信息系统,并利用可辨识矩阵对上下文信息加以约简,进而自动生成规则.由于可供使用的数据有限,所生成的规则无法完全覆盖上下文的取值范围,因此可能出现找不到与上下文状态相匹配规则的问题.为了解决这一问题,提出了一种基于语义距离的规则匹配算法.最后验证了所提出方法的有效性和效率.;To solve the problem that rules in the existing context-aware systems are manually specified by developers or users, an automatic rule generation method is proposed. Context-Aware systems are regarded as decision systems, and context information are reduced with discernibility matrix so as to generate rules. Because the data that can be utilized are limited, the generated rules can not entirely cover the domains of contexts. The rule matches current context probably does not exist. A rule matching algorithm is presented as the solution to this problem. Finally, the efficiency and effectivity of the proposed method is verified.