Continuous process improvement through workstation feedback for General Practice medicine using experts-in-the-loop data mining. This project investigates the iterative use of data mining results to allow experts to construct feedback to influence subsequent production work. We explore the problem in the context of General Practice medicine by having General Practitioners (GPs) review emerging patterns from their own practice's electronic medical records and author feedback to discourage undesi ....Continuous process improvement through workstation feedback for General Practice medicine using experts-in-the-loop data mining. This project investigates the iterative use of data mining results to allow experts to construct feedback to influence subsequent production work. We explore the problem in the context of General Practice medicine by having General Practitioners (GPs) review emerging patterns from their own practice's electronic medical records and author feedback to discourage undesirable patterns. The work will have immediate applicability to medical practice and will drive innovation in data mining method, notably for efficient identification of temporal and complex niche patterns. More broadly, the work will extend the way data mining is used to create new expectations of workstation behaviour.Read moreRead less
The Impact of Information about Data Quality on Decision Making. Data quality problems are widespread in practice and have significant economic impacts. The development of theoretically sound data quality tags and understanding how they impact decision outcomes and processes will lead to improved data quality management within Australian organisations and more efficient and effective decision making. These issues constitute an important area of information technology research. Outcomes from the ....The Impact of Information about Data Quality on Decision Making. Data quality problems are widespread in practice and have significant economic impacts. The development of theoretically sound data quality tags and understanding how they impact decision outcomes and processes will lead to improved data quality management within Australian organisations and more efficient and effective decision making. These issues constitute an important area of information technology research. Outcomes from the project will enhance Australia's research standing and contribute to university teaching and researcher training.Read moreRead less
Efficient Processing of Complex Spatial Queries. Similarity search and join are two of the most popular yet complex queiries in spatial databases. They are also two of the major spatial data analysis paradigms. To complement the existing techniques, this project aims to investigate a more complex and important form of these two problems, and to develop novel framework to approach the proposed problems. The successful achievements of the project will not only bring new spatial data analysis techn ....Efficient Processing of Complex Spatial Queries. Similarity search and join are two of the most popular yet complex queiries in spatial databases. They are also two of the major spatial data analysis paradigms. To complement the existing techniques, this project aims to investigate a more complex and important form of these two problems, and to develop novel framework to approach the proposed problems. The successful achievements of the project will not only bring new spatial data analysis techniques but also deliever effective solutions to a number of real-life apllications.Read moreRead less
Data Enhancement, Integration and Access Services for Smarter, Collaborative and Adaptive Whole-of Water Cycle Management. The project provides a valuable opportunity to make significant impact on water resource management and create community partnerships that will go well beyond the lifetime of the project. The project is expected to contribute to improved water quality and healthier ecosystems. In turn, the scientifically rich research environment will benefit all involved. It will demonstrat ....Data Enhancement, Integration and Access Services for Smarter, Collaborative and Adaptive Whole-of Water Cycle Management. The project provides a valuable opportunity to make significant impact on water resource management and create community partnerships that will go well beyond the lifetime of the project. The project is expected to contribute to improved water quality and healthier ecosystems. In turn, the scientifically rich research environment will benefit all involved. It will demonstrate the capability of the Australian researchers in addressing complex problems in data integration and quality. In particular there will be far reaching benefits of research training for associated PhD students and staff.Read moreRead less
Making sense of trajectory data: a database approach. This project investigates new challenges related to providing functionality, flexibility and efficiency for large scale trajectory data management and processing. The expected outcome includes significant technical contributions in novel indexing structures and advanced query processing methods for making better use of rich trajectory data.
Special Research Initiatives - Grant ID: SR0354744
Funder
Australian Research Council
Funding Amount
$20,000.00
Summary
Improving Australia's Data Mining and Knowledge Discovery Research. The network will bring together over 50 active researchers in data mining and knowledge discovery to enhance and better coordinate Australia's impressive research performance in these dual disciplines. Specifically, the network will (a) facilitate communication and collaboration between researchers, (b) fund or underwrite opportunities for international collaboration, (c) run a number of specialist workshops and symposia and (d ....Improving Australia's Data Mining and Knowledge Discovery Research. The network will bring together over 50 active researchers in data mining and knowledge discovery to enhance and better coordinate Australia's impressive research performance in these dual disciplines. Specifically, the network will (a) facilitate communication and collaboration between researchers, (b) fund or underwrite opportunities for international collaboration, (c) run a number of specialist workshops and symposia and (d) establish a national annual conference.Read moreRead less
Effective Recommendations based on Multi-Source Data. Large-scale data collected from multiple sources such as the Web, sensor networks, academic publications, and social networks provide a new opportunity to exploit useful information for effective and efficient recommendations and decision making. The project will propose a new framework of recommender systems that is based on analysing relationships between different types of objects from multiple data sources. A graph model will be built to ....Effective Recommendations based on Multi-Source Data. Large-scale data collected from multiple sources such as the Web, sensor networks, academic publications, and social networks provide a new opportunity to exploit useful information for effective and efficient recommendations and decision making. The project will propose a new framework of recommender systems that is based on analysing relationships between different types of objects from multiple data sources. A graph model will be built to represent the extracted semantic relationships and novel linkage-analysis based algorithms will be developed for ranking objects. The results from this project will underpin many critical applications such as healthcare.Read moreRead less
BigPrivacy: Scaling privacy preservation for big data applications on cloud. This project aims to research scalable privacy preservation for big data applications on cloud. Privacy preservation is a major concern for big data applications on cloud, such as health data analysis where user privacy must be preserved. Scalable solutions can preserve privacy so that data analysis such as health diagnosis can be performed quickly. The expected deliverable is a unified scalable privacy preservation fra ....BigPrivacy: Scaling privacy preservation for big data applications on cloud. This project aims to research scalable privacy preservation for big data applications on cloud. Privacy preservation is a major concern for big data applications on cloud, such as health data analysis where user privacy must be preserved. Scalable solutions can preserve privacy so that data analysis such as health diagnosis can be performed quickly. The expected deliverable is a unified scalable privacy preservation framework with associated algorithms and its prototype, which cloud systems can deploy for big data applications.Read moreRead less
Federated Cloud Services Configuration and Orchestration. Cloud computing allows organisations to expand or contract their computing footprint based on existing demand. However, existing cloud delivery models support individual segregated and heterogeneous functionalities, which prevent effective coordinated combination of on-premise and off-premise applications, services, and resources. This project aims to significantly contribute to the scientific foundations for the model-driven and elastic ....Federated Cloud Services Configuration and Orchestration. Cloud computing allows organisations to expand or contract their computing footprint based on existing demand. However, existing cloud delivery models support individual segregated and heterogeneous functionalities, which prevent effective coordinated combination of on-premise and off-premise applications, services, and resources. This project aims to significantly contribute to the scientific foundations for the model-driven and elastic configuration and orchestration of resources over heterogeneous cloud services. The outcomes of the project aim to contribute to lifting productivity and economic growth through interoperable and elastic cloud service technologies as well as delivering appropriate skills for the new digital economy.Read moreRead less
Data Exchange and Service Integration with Applications in Health Information Systems. This project will research and develop an innovative new approach to facilitate real data exchange and service integration across different medical organisations. This approach will significantly improve the quality of health care by providing a solid foundation for integrated medical services, offering on demand and effective access to fragmentally stored patients medical information and minimise the number o ....Data Exchange and Service Integration with Applications in Health Information Systems. This project will research and develop an innovative new approach to facilitate real data exchange and service integration across different medical organisations. This approach will significantly improve the quality of health care by providing a solid foundation for integrated medical services, offering on demand and effective access to fragmentally stored patients medical information and minimise the number of data entry errors injected into the medical information systems. The novel integration model will also enable a new autonomous approach for demographic data collection which is essential for evidenced resource allocation, policy making and disease prevention.Read moreRead less