Attribute Oriented Induction High Level Emerging Pattern (AOI-HEP) future research

Abstract

Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) as a new data mining technique, combines two data mining techniques i.e. Attribute Oriented Induction (AOI) and Emerging Patterns (EP). The AOI-HEP application is implemented as a hybrid between AOI characteristic rule mining and HEP algorithms. AOI-HEP combines the powerful features of AOI and EP by using concept hierarchy in AOI to generalize into high level data and applying growth rates in EP and produces powerful discrimination for high level data. AOI-HEP can be implemented to discriminate datasets such as finding bad and good customers for banking loan systems or credit card applicants and etc. Meanwhile, AOI-HEP can be implemented to mine similar patterns such as similar customer loan patterns or similar customer credit card rating and etc. Since AOI-HEP is a new data mining technique, then future research can be explored such as inverse discovery learning, learning more than two datasets, learning other knowledge rules and etc. AOI-HEP future research will give research idea for data mining researchers community particularly for bachelor and master degree students. Indeed, AOI-HEP as new comer data mining technique will be completed in discovery process, having rich interesting patterns and become interested mining technique.