CAJ | 학술논문

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.
제출료상하문기억모형이급진행상하문사순화관련관계발현적방법.상하문사순방법기우RDF수거집화SPARQL어언.위료진행협작관련관계적발현,제출료일충장RDF구명도전환위"상하문도(context graph)"적방법,수선용통계분석적방법대"상하문도"중절점중요성이급변적권치진행정의,연후장격활확산산법(spread activation)응용재해상하문도중.최후급출료해방법재협작상하문공간(CCS)계통중응용적광가실례,해계통용래지지협작배경중적상하문기억사순화협작관련관계발현.
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.