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IJML 2012 Vol.2(3): 287-291
doi: 10.7763/IJMLC.2012.V2.132

Context Modeling and Measuring for Context Aware Knowledge Management

Ke Ning1 , David O’Sullivan2

  • 1High-tech Industrial Park, Nanshan, Shenzhen, China.
  • 2National University of Ireland, Galway,Ireland

Abstract

To fully understand and to better reuse knowledge, it’s necessary to correlate knowledge with the context under which the knowledge is generated and managed. However, it remains a challenge to support context awareness in knowledge management system. This paper tries to overcome the difficulties by introducing key enabling technologies for context modeling and measuring: The knowledge context ontology correlates knowledge and its contexts through a high level activity based model is defined; The algorithm for Context similarity measurement is designed by exploiting the hierarchical domain structure defined in the context model.

Keywords

  • Context aware
  • context modeling
  • knowledge management
  • similariy measure
132-I30107

How to Cite

Copied

Ke Ning and David O’Sullivan, "Context Modeling and Measuring for Context Aware Knowledge Management," International Journal of Machine Learning, vol. 2, no. 3, pp. 287-291, 2012. https://doi.org/10.7763/IJMLC.2012.V2.132

Copyright & License

Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • DOI: 10.18178/IJML
  • Frequency: Quarterly
  • Average Days to Accept: 68 days
  • Acceptance Rate: 27%
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • DOI: 10.18178/IJML
  • Abstracing/Indexing: Google Scholar, Crossref, ProQuest, Electronic Journals Library, CNKI.
  • E-mail: editor@ijml.org
  • APC: 500USD