Title: Collective memory based on semantic annotation among economic intelligence actors

Authors: Bensattalah Aissa; Fahima Nader; Rachid Chalal

Addresses: National High School for Computer Science (E.S.I), 16000 Oued-Smar, Algiers, Algeria; National Institute of 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

Abstract: Many enterprises are reflected on strategies and tools that facilitate the knowledge sharing and exploiting the collective intelligence among their actors. Economic intelligence actors collaborate to solve a decisional problem, they use significant mental effort, and so they share a common knowledge that can indicate to other actors directions to follow or avoid. Indeed, whenever an actor explores knowledge or a relevant document, it enriches the collective knowledge of the memory via annotations. To ensure this collaboration in solving a decisional problem among actors in a context of economic intelligence, in this article we propose a conceptual model using ontologies to represent collaborative semantic annotations between economic intelligence actors in order to capitalise on and reuse the knowledge shared in a collective memory.

Keywords: economic intelligence; semantic annotation; collective memory; ontology; modelling; interaction meaning; knowledge capitalisation; knowledge reuse; collective intelligence management; collaborative problem solving; collaboration; knowledge sharing.

DOI: 10.1504/IJCI.2014.064850

International Journal of Collaborative Intelligence, 2014 Vol.1 No.1, pp.18 - 32

Received: 02 Aug 2013
Accepted: 13 Nov 2013
Published online: 27 Sep 2014 *