The Data Mining OPtimization Ontology

Keet, C. Maria and Lawrynowicz, Agnieszka and d'Amato, Claudia and Kalousis, Alexandros and Nguyen, Phong and Palma, Raul and Stevens, Robert (2015) The Data Mining OPtimization Ontology, Web Semantics: Science, Services and Agents on the World Wide Web, 32, 43-53, Elsevier.

[img] PDF

Download (547kB)


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.

Item Type: Journal article (paginated)
Uncontrolled Keywords: Data mining, ontology development, semantic web
Subjects: Computing methodologies > Artificial intelligence
Computing methodologies > Modeling and simulation
Date Deposited: 08 Jul 2015
Last Modified: 10 Oct 2019 15:32

Actions (login required)

View Item View Item