About DMOP

To cite DMOP

To cite the latest version, please use:

ref TBA for v5.5

To cite v5.3, please use:

Keet, C.M., Lawrynowicz, A., d'Amato, C., Hilario, M. Modeling issues and choices in the Data Mining OPtimisation Ontology. 10th Workshop on OWL: Experiences and Directions (OWLED'13), 26-27 May 2013, Montpellier, France. CEUR-WS vol 1080.

To cite an older version of DMOP (status of DMOP in 2010), please use:

M. Hilario, P. Nguyen, H. Do, A. Woznica, A. Kalousis. Ontology-based meta-mining of knowledge discovery workflows. In N. Jankowski et al., Meta-Learning in Computational Intelligence, Springer, 2011, pp271-315.

 

Recent publications about DMOP or using DMOP (by one or more DMOP developer)

Nguyen, P. Hilario, M. Kalousis, A. Using meta-mining to support data mining workflow planning and optimization. Journal of Artificial Intelligence Research (in print).

Kietz, J-U., Serban, F., Fischer, S., Bernstein, A. "Semantics Inside!" But Let's Not Tell the Data Miners: Intelligent Support for Data Mining. The Semantic Web: Trends and Challenges - 11th International Conference, ESWC 2014, Anissaras, Crete, Greece, May 25-29, 2014. Proceedings. Springer LNCS vol. 8465, pp706-720.

Keet, C.M., d'Amato, C., Khan, Z.C., Lawrynowicz, A. Exploring Reasoning with the DMOP Ontology. 3rd Workshop on Ontology Reasoner Evaluation (ORE'14). Samantha Bail, S., Glimm, B, Jimenez-Ruiz, E., Matentzoglu, N., Parsia, B., Steigmiller, A. (Eds.). July 13, 2014, Vienna, Austria. CEUR-WS Vol 1207, 64-70.

Keet, C.M., Lawrynowicz, A., d'Amato, C., Hilario, M. Modeling issues and choices in the Data Mining OPtimisation Ontology. 10th Workshop on OWL: Experiences and Directions (OWLED'13), 26-27 May 2013, Montpellier, France. CEUR-WS vol 1080.

more refs TBA

e-Lico publications (including DMOP) up to 2011

 

Users around the world

Panov, P., Soldatova, L., Dzeroski, S.. Ontology of core data mining entities. Data Min Knowl Discov 2014; 28(5-6):1222–1265.

Vanschoren, J., Blockeel, H., Pfahringer, B., Holmes, G.. Experiment databases. A new way to share, organize and learn from experiments. Machine Learning 2012;87(2):127–158.

Vanschoren, J.. Meta-learning architectures. Collecting, organizing and exploiting meta-knowledge. In: Grabczewski, K., Wlodzislaw, D., Jankowski, N., editors. Meta-Learning in Computational Intelligence; vol. 358 of Studies in Computational Intelligence. Springer; 2011, p. 117–155.

more refs TBA

Papers citing DMOP

 

Contact us

Please contact us by sending an email to:

info at dmo-foundry.org

 

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