The University of Queensland

Mining Distributed High-Speed Time-Variant Data Streams (2005–2007)

Abstract:

In the current computing environment different types of networks are connected to data sources. Data content is often hidden in data streams rather than in static data collections. The mining of dynamically changing time variant data streams presents new challenges. There is an expectation to deliver accurate knowledge discovery in an efficient way in order to provide instant decision support. This project aims to investigate selected aspects of the new generation of data mining problems; consider maintenance-based methods for rules and patterns discovery provide a comparative study on different solutions and investigate methods of data transformation that convert multiple distributed data streams into a data-mining-ready structure

Grant type:

ARC Discovery Projects

Researchers:

• 

  Professor Xue Li

  Professor
  

  School of Electrical Engineering and Computer Science

  Faculty of Engineering, Architecture and Information Technology

Funded by:

Australian Research Council