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

Authors: Bensattalah Aissa; Faiçal Azouaou; Fahima Nader; Rachid Chalal

Addresses: National High School for Computer Science (E.S.I), 16000 Oued-Smar, Algiers, Algeria; Department of Science and Technology, BP 78 Zaaroura, 14000 Tiaret, Algeria ' National High School for Computer Science (E.S.I), 16000 Oued-Smar, Algiers, Algeria ' National High School for Computer Science (E.S.I), 16000 Oued-Smar, Algiers, Algeria ' National High School for Computer Science (E.S.I), 16000 Oued-Smar, Algiers, Algeria

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.

Keywords: economic intelligence; decision support process; unstructured decision problem; ontology; semantic annotation; context; adaptation; annotation tool.

DOI: 10.1504/IJBIS.2018.094693

International Journal of Business Information Systems, 2018 Vol.29 No.2, pp.207 - 232

Received: 02 Oct 2016
Accepted: 07 Jan 2017
Published online: 12 Sep 2018 *

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