Various rules can be generated from databases by using association rule algorithms, but only a small number of these rules may be selected for implementation due to the limitations of resources. Accordingly, evaluating the quality of these rules becomes a hot topic in the data mining field. Based on multiple criteria decision theory, a framework for evaluating the mined association rules using ...

Outlier Mining has always attract much attention among the data mining community. This paper discusses on the discovery of meaningful outlier detection based on Non_Reduct computation by incorporating the Negative Association Rules. Non_Reduct computation is proposed to detect outliers from rare classes. These outliers may have meaningful knowledge having incorporating the concept of Negatives ...

In the present paper, we propose a Neuroelectromagnetic Ontology Framework (NOF) for mining Event-related Potentials (ERP) patterns as well as the process. The aim for this research is to develop an infrastructure for mining, analysis and sharing the ERP domain ontologies. The outcome of this research is a Neuroelectromagnetic knowledge-based system. The framework has 5 stages: 1) Data pre-proc...