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EI-Annotate: an adaptive collective memory based on annotation ontology and context for decision making in economic intelligence

Author

Listed:
  • Bensattalah Aissa
  • Faiçal Azouaou
  • Fahima Nader
  • Rachid Chalal

Abstract

In the decision support process, the economic intelligence actors use mental efforts and considerable cognitive activities to solve decisional problems; they deal with a large mass of digital documents during their activities. To facilitate their activities, they use different types of annotations on the manipulated document. To exploit the benefits of these annotations, we propose in this paper, EI-Annotate, an annotation tool dedicated to economic intelligence actors, which enables them to create an adaptive collective memory. The adaptive collective memory based on annotation ontology and context suitable for economic intelligence. This memory is a knowledge management tool that can support economic intelligence actors in their decision process. The EI-Annotate annotation module is implemented as extensions using different technologies; it enables to annotate resources in different formats (document, picture, videos). We present the results of an evaluation study of the proposed architecture of an adaptive collective memory conducted with a research laboratory context, regarding their annotation experience using EI-Annotate.

Suggested Citation

  • Bensattalah Aissa & Faiçal Azouaou & Fahima Nader & Rachid Chalal, 2018. "EI-Annotate: an adaptive collective memory based on annotation ontology and context for decision making in economic intelligence," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 29(2), pages 207-232.
  • Handle: RePEc:ids:ijbisy:v:29:y:2018:i:2:p:207-232
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