Data Mining Ontologies

, Last updated by hilario, on Fri, 01/14/2011 - 12:37

e-LICO Data Mining Ontology (DMO)

The e-LICO Data Mining Ontology (DMO) serves a number of different objectives; it has been modularized in order to ensure quick, goal-oriented development.

One objective is to support planning of the knowledge discovery process and building of workflows for a user task. This is being pursued through the e-LICO Protégé-based planning and Data Mining Work Flow (eProPlan-DMWF) Ontology.

The second objective is to support algorithm and model selection for data mining tasks that require search in the space of possible methods and models, e.g., feature selection or induction (modelling).  The third objective is to support meta-mining, or learning from data mining experimentation records to improve algorithm and model selection for search-intensive tasks. The ontology for Data Mining Optimization (DMOP) is being developed in pursuit of these last two objectives.