Ontology-guided intelligent data mining assistance: Combining declarative and procedural knowledge.

Abstract

The effective application of a data mining process is littered with many difficult and technical decisions (i.e. data cleansing, feature transformations, algorithms, parameters, evaluation). Subsequently, most data mining products provide a large number of models and tools, but few provide intelligent assistance for addressing the above-mentioned challenges that face the non-specialist data miner. In this paper, we propose the realization of a hybrid intelligent data mining assistant, based on the synergistic combination of both declarative (Description Logic) and procedural (SWRL Rules) ontology knowledge in order to empower the non-specialist data miner throughout the key phases of the CRISP-DM data mining process.