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Authors: Mounir Kehal ; Sandrine Crener and Patrice Sargenti

Affiliation: CSITDS Research Group International University of Monaco, Monaco

Keyword(s): Knowledge Management, Knowledge Maps, Neural Networks, Organizational Cartography, Semantic Relevance, Unsupervised learning, Kohonen Networks, Self-Organizing Maps (SOMs).

Related Ontology Subjects/Areas/Topics: Advanced Applications of Fuzzy Logic ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Data Engineering ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Natural Language Interfaces to Intelligent Systems ; Ontologies and the Semantic Web ; Society, e-Business and e-Government ; Verification and Validation of Knowledge-Based Systems ; Web Information Systems and Technologies

Abstract: The Post-Globalization aeon has placed businesses everywhere in new and different competitive situations where knowledgeable, effective and efficient behaviour has come to provide the competitive and comparative edge. Enterprises have turned to explicit- and even conceptualising on tacit- Knowledge Management to elaborate a systematic approach to develop and sustain the Intellectual Capital needed to succeed. To be able to do that, you have to be able to visualize your organization as consisting of nothing but knowledge and knowledge flows, whilst being presented in a graphical and visual framework, referred to as automated organizational cartography. Hence, creating the ability of further actively classifying existing organizational content evolving from and within data feeds, in an algorithmic manner, hence potentially giving insightful schemes and dynamics by which organizational know-how is visualised. It is discussed and elaborated on most recent and applicable definitions and classifications of knowledge management, representing a wide range of views from mechanistic (systematic, data driven) to a more socially (psychologically, cognitive/metadata driven) orientated. More elaborate continuum models, for knowledge acquisition and reasoning purposes, are being used for effectively representing the domain of information that an end user may contain in their decision making process for utilization of available organizational intellectual resources. (More)

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Paper citation in several formats:
Kehal, M.; Crener, S. and Sargenti, P. (2006). LOCATING KNOWLEDGE THROUGH AUTOMATED ORGANIZATIONAL CARTOGRAPHY [AUTOCART]. In Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-972-8865-42-9; ISSN 2184-4992, SciTePress, pages 351-355. DOI: 10.5220/0002467903510355

@conference{iceis06,
author={Mounir Kehal. and Sandrine Crener. and Patrice Sargenti.},
title={LOCATING KNOWLEDGE THROUGH AUTOMATED ORGANIZATIONAL CARTOGRAPHY [AUTOCART]},
booktitle={Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2006},
pages={351-355},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002467903510355},
isbn={978-972-8865-42-9},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Eighth International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - LOCATING KNOWLEDGE THROUGH AUTOMATED ORGANIZATIONAL CARTOGRAPHY [AUTOCART]
SN - 978-972-8865-42-9
IS - 2184-4992
AU - Kehal, M.
AU - Crener, S.
AU - Sargenti, P.
PY - 2006
SP - 351
EP - 355
DO - 10.5220/0002467903510355
PB - SciTePress