Drift learning for decision-making in dynamic multi-stream environments

点击翻译按钮获取中文摘要

This project aims to provide application-ready real-time decision support systems for big data situations. Real-time support for organisational decisions is crucial in fast-changing environments that are highly dependent on data from multiple large streams. Unforeseen changes in data distribution (drift) are inevitable. The ability to learn drift in dynamic environments with multiple large data streams will benefit innovation and decision quality in challenging data situations. The project will have wide applications, such as in cybersecurity, telecommunications, bushfire control and logistics. The project will advance machine learning knowledge, providing a foundation and technologies to support real-time decision-making in big data environments.