基于描述逻辑的上下文知识获取与推理方法

摘要

针对上下文感知计算中缺乏清晰统一的模型与自动推理支持的问题,提出一种基于描述逻辑的上下文知识获取与推理方法.该方法首先提出了一种本体引导的上下文模型框架,根据抽象层次的不同将上下文模型分为元模型与领域特定模型两层结构；然后采用描述逻辑表示语言SHOIN(D)形式化描述该上下文模型,设计上下文模型向描述逻辑知识库的转换算法.最后以一个实际案例说明该方法的可行性.%Aiming at the problem of uncertain model and lack of automatic reason reasoning support in context-aware technique,the paper proposed an approach to model and reason the context-aware knowledge based on description logic. It suggests a context model framework in the semantic restrictions of the ontology, which divides the context model into two-level structure as meta ontology and domain-specific ontology,according to the abstract hierarchy. The objectives of our model framework include modeling a set of high-level entities, and providing flexible extensibility to add specific concepts in different application domains. After that, the paper proposed an algorithm to convert the context model to the knowledge described in description logic using SHOIN(D). Finally,a case study was given to illustrate the practicality of the method.