Experiences with a Logic-Based Knowledge Discovery Support Environment

We introduce a Logic-Based Knowledge Discovery Support Environment, capable of integrating knowledge extraction and knowledge manipulation. Its flexibility and expressiveness in supporting the process of knowledge discovery in databases is illustrated by presenting two case studies, market-basket analysis and audit planning strategy in fraud detection. We show that the query language deals effectively and uniformly with data preparation, model extraction and model evaluation and analysis, thus providing a powerful formalism where methodologies for classes of challenging applications can be conveniently designed.