A multi-strategy knowledge interoperability framework for heterogeneous learning objects

This paper presents a knowledge exchange framework that can leverage the interoperability among semantically heterogeneous learning objects. With the release of various e-Learning standards, learning contents and digital courses are easy to achieve cross-platform sharing, exchanging, and even reorga...

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Veröffentlicht in:	Expert systems with applications 2011-05, Vol.38 (5), p.4945-4956
Hauptverfasser:	Lee, Ming Che, Tsai, Kun Hua, Hsieh, Tung Cheng
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Classification Digital Heterogeneous databases Interoperability Knowledge bases (artificial intelligence) Learning Ontology Semantics
Online-Zugang:	Volltext
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