中文摘要：

提出了上下文记忆模型以及进行上下文查询和关联关系发现的方法．上下文查询方法基于RDF数据集和SPARQL语言．为了进行协作关联关系的发现，提出了一种将RDF具名图转换为“上下文图（context graph）”的方法，首先用统计分析的方法对“上下文图”中节点重要性以及边的权值进行定义，然后将激活扩散算法（spread activation）应用在该上下文图中．最后给出了该方法在协作上下文空间（CCS）系统中应用的框架实例，该系统用来支持协作环境中的上下文记忆查询和协作关联关系发现．

英文摘要：

A context memory model and an approach for context query and association discovery are proposed. The context query is based on a resource description framework （RDF） dataset and SPARQL language. To discover collaborative associations, an approach of transforming RDF named graphs into ＂context graph＂ is proposed. First, the definitions of the importance of the nodes and the weight assignment for the ＂context graph＂ are given. Secondly, the implementation of a spread activation algorithm based on ＂context graph＂ is proposed. An infrastructure is also built up in the collaborative context space （CCS） system to support context memory and knowledge discovery in a collaborative environment.