Personalised Ontology Learning and Mining for Web Information Gathering. The project will provide a flexible framework for a sound theoretical model of personalised systems. It will significantly influence the development of personalised Web services and many leading industry organisations that attempt to deliver personalised services to their valuable customers. The proposed project will also strengthen the pre-existing international collaboration networks. It will establish Australian researc ....Personalised Ontology Learning and Mining for Web Information Gathering. The project will provide a flexible framework for a sound theoretical model of personalised systems. It will significantly influence the development of personalised Web services and many leading industry organisations that attempt to deliver personalised services to their valuable customers. The proposed project will also strengthen the pre-existing international collaboration networks. It will establish Australian researchers leading position in the related research fields and communities, and provide an established paradigm for other researchers to follow. In addition, the project will provide significant contributions to Australian National Research Priority in the areas of Smart Information Use.Read moreRead less
Privacy preserving data sharing in data mining environments. Preserving privacy in data mining among various enterprises and organisations is essential for many real world applications in areas like health surveillance, business analysis, fraud detection and terror protection. Efficient and effective techniques are badly needed to protect privacy in data sharing and data mining. The developed cutting-edge techniques in this project will be implemented in freely available open source software too ....Privacy preserving data sharing in data mining environments. Preserving privacy in data mining among various enterprises and organisations is essential for many real world applications in areas like health surveillance, business analysis, fraud detection and terror protection. Efficient and effective techniques are badly needed to protect privacy in data sharing and data mining. The developed cutting-edge techniques in this project will be implemented in freely available open source software tools, empowering Australian organisations to utilise the techniques to develop intelligent systems in data sharing environments. These techniques will ultimately lead to better utilisation of the information available in many enterprises and organisations.Read moreRead less
Efficient Similarity Query Processing in High Dimensional Databases. This project studies a fundamental problem common to a wide range of applications. It contributes to smart use of information, which is vital to the modern knowledge-based economy, by providing an enabling technology to capitalise Australia's huge investment in data collection. Our research is right in the forefront of ICT research, leading the international effort of extending database technologies to support data management a ....Efficient Similarity Query Processing in High Dimensional Databases. This project studies a fundamental problem common to a wide range of applications. It contributes to smart use of information, which is vital to the modern knowledge-based economy, by providing an enabling technology to capitalise Australia's huge investment in data collection. Our research is right in the forefront of ICT research, leading the international effort of extending database technologies to support data management and query processing for very large and highly complex data.Read moreRead less
Context Exploration: An Effective Way to Enhance Duplication Detection. As a vital data quality problem, effective duplication detection has practical significance in data management, in particular in large scale information systems such as in business, health and national security. This project aims to be a unique value to virtually every information systems by providing a general, domain-independent framework which is comprehensive to significantly improve the duplication detection. The develo ....Context Exploration: An Effective Way to Enhance Duplication Detection. As a vital data quality problem, effective duplication detection has practical significance in data management, in particular in large scale information systems such as in business, health and national security. This project aims to be a unique value to virtually every information systems by providing a general, domain-independent framework which is comprehensive to significantly improve the duplication detection. The developed cutting-edge technologies are potential to be a new direction of data duplication detection study. This project will allow us to avail an opportunity to promote Australia's capability in developing sophisticated technologies and are potential to add to Australia's profile in this area. Read moreRead less