Optimization of semantic MASHUP architecture applied in microlearning enivironment
1.Applied Telematics/e-Business Group,University of Leipzig,Leipzig 04109,Germany;2.School of Computer Science and Technology,Jiangsu Teachers University of Technology,Changzhou,Jiangsu 213001,China
Abstract: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.