The Data Mining OPtimization Ontology

Keeta, C. Maria (Department of Computer Science, University of Cape Town, South Africa) ; Ławrynowiczb, Agnieszka (Institute of Computing Science, Poznan University of Technology, Poland) ; d’Amato, Claudia (Department of Computer Science, University of Bari, Italy) ; Kalousis, Alexandros (Haute école de gestion de Genève, HES-SO // Haute Ecole Spécialisée de Suisse Occidentale) ; Nguyen, Phong (Department of Computer Science, University of Geneva, Switzerland) ; Palma, Raul (Poznan Supercomputing and Networking Center, Poland) ; Stevens, Robert (School of Computer Science, University of Manchester, United Kingdom) ; Hilario, Melanie (Artificial Intelligence Laboratory, University of Geneva, Switzerland)

The Data Mining OPtimization Ontology (DMOP) has been developed to support informed decision-making at various choice points of the data mining process. The ontology can be used by data miners and deployed in ontology-driven information systems. The primary purpose for which DMOP has been developed is the automation of algorithm and model selection through semantic meta-mining that makes use of an ontology-based meta-analysis of complete data mining processes in view of extracting patterns associated with mining performance. To this end, DMOP contains detailed descriptions of data mining tasks (e.g., learning, feature selection), data, algorithms, hypotheses such as mined models or patterns, and workflows. A development methodology was used for DMOP, including items such as competency questions and foundational ontology reuse. Several non-trivial modeling problems were encountered and due to the complexity of the data mining details, the ontology requires the use of the OWL 2 DL profile. DMOP was successfully evaluated for semantic meta-mining and used in constructing the Intelligent Discovery Assistant, deployed at the popular data mining environment RapidMiner


Mots-clés:
Type d'article:
scientifique
Faculté:
Economie et Services
Ecole:
HEG GE Haute école de gestion de Genève
Institut:
CRAG - Centre de Recherche Appliquée en Gestion
Classification:
Informatique
Date:
2015
Pagination:
10 p.
Titre du document hôte:
Journal of web semantics
Numérotation (vol. no.):
2015, vol. 32, pp. 43-53
DOI:
ISSN:
1570-8268
Le document apparaît dans:



 Notice créée le 2015-11-19, modifiée le 2018-04-09

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