Authors
C Maria Keet, Agnieszka Ławrynowicz, Claudia d’Amato, Alexandros Kalousis, Phong Nguyen, Raul Palma, Robert Stevens, Melanie Hilario
Publication date
2015/5/1
Journal
Journal of web semantics
Volume
32
Pages
43-53
Publisher
Elsevier
Description
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 …
Total citations
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Scholar articles
CM Keet, A Ławrynowicz, C d'Amato, A Kalousis… - Journal of web semantics, 2015