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Agent mining approaches: an ontological view

Published online by Cambridge University Press:  31 August 2021

Emmanuelle Grislin-Le Strugeon*
Affiliation:
Univ. Polytechnique Hauts-de-France, LAMIH, CNRS, UMR 8201, F-59313 Valenciennes, France INSA Hauts-de-France, F-59313 Valenciennes, France
Kathia Marcal de Oliveira*
Affiliation:
Univ. Polytechnique Hauts-de-France, LAMIH, CNRS, UMR 8201, F-59313 Valenciennes, France
Dorsaf Zekri*
Affiliation:
Univ. Polytechnique Hauts-de-France, LAMIH, CNRS, UMR 8201, F-59313 Valenciennes, France ReDCAD Laboratory, University of Sfax, B.P. 1173, 3029 Sfax, Tunisia
Marie Thilliez*
Affiliation:
Univ. Polytechnique Hauts-de-France, LAMIH, CNRS, UMR 8201, F-59313 Valenciennes, France

Abstract

Introduced as an interdisciplinary area that combines multi-agent systems, data mining and knowledge discovery, agent mining is currently in practice. To develop agent mining applications involves a combination of different approaches (model, architecture, technique and so on) from software agent and data mining (DM) areas. This paper presents an investigation of the approaches used in the agent mining systems by deeply analyzing 121 papers resulting from a systematic literature review. An ontology was defined to capitalize the knowledge collected from this study. The ontology is organized according to seven main facets: the problem addressed, the application domain, the agent-related and the mining-related elements, the models, processes and algorithms. This ontology is aimed at providing support to decisions about agent mining application design.

Type
Review
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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