Research on learning resources grid information retrieval based on metadata

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Abstract

Huge, dynamic and heterogeneous resources are difficult to achieve full sharing because of lacking comprehensive and uniform description format and interaction norms. In this paper, the grid and metadata technology is adopted to solve this problem. First, the layered metadata model is proposed on the basis of hierarchical structure of LRG. All irregular resources are divided into five layers using metadata technology: resource metadata layer, information transmission metadata layer, virtual organization metadata layer, service metadata layer and user metadata layer. Second, referring to domestic and foreign experiences of metadata norms, the description schemes about resource metadata, service metadata and user metadata are presented. Finally, the middleware tool-Alchemi is adopted to simulate and build the LRG system. Retrieval of resource, service and user information in LRG is realized and the proposed metadata schemes are testified to be feasible, valid, practical and significant in theory and application. © 2012 Springer-Verlag GmbH.

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Yang, L., Zhong, L., & Zhu, B. (2012). Research on learning resources grid information retrieval based on metadata. In Advances in Intelligent and Soft Computing (Vol. 169 AISC, pp. 413–418). https://doi.org/10.1007/978-3-642-30223-7_64

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