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Authors: Rim Ayadi 1 ; Yasser Hachaichi 1 ; Saleh Alshomrani 2 and Jamel Feki 3

Affiliations: 1 Multimedia, InfoRmation Systems and Advanced, Computing Laboratory and University of Sfax, Tunisia ; 2 University of Jeddah, Saudi Arabia ; 3 Multimedia, InfoRmation Systems and Advanced, Computing Laboratory and University of Jeddah, Tunisia

ISBN: 978-989-758-096-3

Keyword(s): Heterogeneous Knowledge, Knowledge Harmonization, Knowledge Warehouse, Data Mining, MOT, Metamodels, Transformation Rules, Source Model, Target Model.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Group Decision Support Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Ontologies and the Semantic Web ; Sensor Networks ; Signal Processing ; Society, e-Business and e-Government ; Soft Computing ; Web Information Systems and Technologies

Abstract: Explicit knowledge extracted from data, formalized tacit knowledge from experts or even knowledge existing in business sources may be in several heterogeneous formal representations and structures: as rules, models, functions, etc. However, a knowledge warehouse should solve this structural heterogeneity before storing knowledge. This requires specific tasks of harmonizing. This paper first presents our proposed definition and architecture of a knowledge warehouse, and then presents some languages for knowledge representations as particular the MOT (Modeling with Object Types) language. In addition, we suggest a metamodel for the MOT, and a metamodel for the explicit knowledge obtained using decision trees technique. As we aim to represent knowledge having different modeling formalisms into MOT, as a unified model, then we suggest a set of transformation rules that assure the move from the decision tree source model into the MOT target model. This work is still in progress, it is curr ently completed with tranformations for additional. (More)

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Paper citation in several formats:
Ayadi, R.; Hachaichi, Y.; Alshomrani, S. and Feki, J. (2015). Decision Tree Transformation for Knowledge Warehousing.In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-096-3, pages 616-623. DOI: 10.5220/0005380506160623

@conference{iceis15,
author={Rim Ayadi. and Yasser Hachaichi. and Saleh Alshomrani. and Jamel Feki.},
title={Decision Tree Transformation for Knowledge Warehousing},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2015},
pages={616-623},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005380506160623},
isbn={978-989-758-096-3},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Decision Tree Transformation for Knowledge Warehousing
SN - 978-989-758-096-3
AU - Ayadi, R.
AU - Hachaichi, Y.
AU - Alshomrani, S.
AU - Feki, J.
PY - 2015
SP - 616
EP - 623
DO - 10.5220/0005380506160623

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