摘要
针对目前MASHUP应用中非语义实现过程的弱描述性、低复用性等问题,探究当前微学习环境下MASHUP架构的语义实现方式并加以优化改进.基于分析以学习者为组织中心的微学习(microlearning)模式的内涵外延,论证了通过MASHUP网络聚合架构高效提取及有效整合网络中松散分布的同主题微内容的可能性.提出一种构建资源群组主题自动匹配的Net-Node网络混搭模型,通过资源子网内资源属性的路由搜索和串联匹配,实现微学习中MASHUP应用的微内容完全语义封装.
Considering the drawbacks during the syntax procedure in application of MASHUP,such as weak descriptive capability and lower reusability,a semantic realization methodology of MASHUP architecture under current microlearning environment was studied and optimized.Based on the analysis of intension and extension of microlearning model,in which learner was the organization center,it was demonstratedthat using MASHUP network aggregation architecture could effectively extract and integrate semantic-related microcontent.An advanced MASHUP architecture named Net-Node,in which resource group was automatically matched by subject,was proposed and evaluated.In this model,entire semantic encapsulation of microcontent in MASHUP applications under microlearning was completed by means of attribute routing and serial matching in the MASHUP net.
出处
《江苏大学学报（自然科学版）》
EI
CAS
北大核心
2010年第3期339-342,共4页
Journal of Jiangsu University：Natural Science Edition
基金
Deutschen TELCOM AG基金资助项目
