Data-Driven Decision Support

In this position paper, we propose a framework for adaptive \(D3\)M under concept drift in high-volume streaming data environment, elaborate the challenges and opportunities presented by big streaming data, introduce the three steps of learning under concept drift, and discuss future research directions for adaptive decision support.

This paper highlights the issue of real-time \(D3\)M and provides some fundamental knowledge and methodologies for researchers and practitioners in decision support system area. We hope it could provide a good guideline on how to apply concept drift handling methodologies to help \(D3\)M techniques in big streaming data.