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ALOA: A Web Services Driven Framework for Automatic Learning Object Annotation

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Part of the Lecture Notes in Computer Science book series (LNPSE,volume 5192)

Abstract

Generating learning object metadata is a complex task to be done manually. An automated approach is therefore required. This work presents the concepts and ideas behind the automatic generation of metadata. We propose a Web Services driven framework for IEEE LOM-compliant automatic learning object annotation called ALOA. The primary focus has been on the flexibility and extensibility of the framework, such that new metadata generation services can easily be plugged into the basic system.

Keywords

  • Metadata Standard
  • UDDI Registry
  • Party Application
  • Metadata Generation
  • Learn Object Metadata

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-540-87605-2_10
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References

  1. PROLEARN Network of Excellence, http://www.prolearn-project.org/

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© 2008 Springer-Verlag Berlin Heidelberg

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Chatti, M.A., Muhammad, N.F., Jarke, M. (2008). ALOA: A Web Services Driven Framework for Automatic Learning Object Annotation. In: Dillenbourg, P., Specht, M. (eds) Times of Convergence. Technologies Across Learning Contexts. EC-TEL 2008. Lecture Notes in Computer Science, vol 5192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87605-2_10

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  • DOI: https://doi.org/10.1007/978-3-540-87605-2_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87604-5

  • Online ISBN: 978-3-540-87605-2

  • eBook Packages: Computer ScienceComputer Science (R0)