Exploring Reasoning with the DMOP Ontology
Authors: C. Maria Keet, Claudia D'Amato, Zubeida Khan and Agnieszka Lawrynowicz
Paper Information
| Title: | Exploring Reasoning with the DMOP Ontology |
| Authors: | C. Maria Keet, Claudia D'Amato, Zubeida Khan and Agnieszka Lawrynowicz |
| Proceedings: | ORE 2014 Proceedings |
| Editor: | Ernesto Jimenez-Ruiz |
| Keywords: | data mining ontology, reasoner performance, inverse properties, modularization |
| Abstract: | ABSTRACT. We describe the Data Mining OPtimization Ontology (DMOP), which was developed to support informed decision-making at various choice points of the knowledge discovery (KD) process. DMOP contains in-depth descriptions of DM tasks, data, algorithms, hypotheses, and workflows. Its development raised a number of non-trivial modeling problems, the solution to which demanded maximal exploitation of OWL 2 representational potential. The choices made led to v5.4 of the DMOP ontology. We report some evaluations on processing DMOP with a standard reasoner by considering different DMOP features. |
| Pages: | 0 |
| Talk: | Jul 13 14:30 |
| Paper: | ![]() |
