Transaction Oriented Computational Models for Multi Agent Systems. Agent systems are a very promising technology for constructing complex, large-scale software. Australian researchers have made key
contributions in this area, particularly with reference to one mature and commonly adopted agent architecture known as BDI (Belief, Desire, Intention). To make this technology suitable for use in advanced applications, it has to be provided with robust and predictable behaviour. This project wil ....Transaction Oriented Computational Models for Multi Agent Systems. Agent systems are a very promising technology for constructing complex, large-scale software. Australian researchers have made key
contributions in this area, particularly with reference to one mature and commonly adopted agent architecture known as BDI (Belief, Desire, Intention). To make this technology suitable for use in advanced applications, it has to be provided with robust and predictable behaviour. This project will address that need by designing and implementing a novel agent language for BDI, based on contributions using transactional concepts for agents developed at The University of Melbourne. This will contribute to the development of robust and predictable agent software, that can be used in complex and large scale applications of the future.
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Efficient Strategies for Mining Negative Association Rules. Negative association rules (NAR) catch mutually-exclusive correlations
among items. They play important roles just as traditional association
rules (TAR) do. For example, in stock market surveillance based on alert logs, NARs detect which alerts are false. There are essential differences between mining TARs and NARs because NARs are hidden in infrequent itemsets. This research will develop efficient strategies for mining NARs in datab ....Efficient Strategies for Mining Negative Association Rules. Negative association rules (NAR) catch mutually-exclusive correlations
among items. They play important roles just as traditional association
rules (TAR) do. For example, in stock market surveillance based on alert logs, NARs detect which alerts are false. There are essential differences between mining TARs and NARs because NARs are hidden in infrequent itemsets. This research will develop efficient strategies for mining NARs in databases. These strategies are expected to be about ten times faster than existing ones. This project will deliver database-independent and high-performance mining algorithms for decision-making. The results can benefit Australian marketing and financial companies as well as health and security departments for smart information use.Read moreRead less
Multiple Data Source Discovery: Group Interaction Approach. This project will develop new technology and theory to identify and evaluate incomplete data. It will deliver a high-performance group-interaction based global pattern discovery system that enables decision-makers (like doctors) to access valuable implicit information that is contained in their data but not currently accessible. Mining group interactions will greatly extend the scope of pattern discovery and new product evaluation. The ....Multiple Data Source Discovery: Group Interaction Approach. This project will develop new technology and theory to identify and evaluate incomplete data. It will deliver a high-performance group-interaction based global pattern discovery system that enables decision-makers (like doctors) to access valuable implicit information that is contained in their data but not currently accessible. Mining group interactions will greatly extend the scope of pattern discovery and new product evaluation. The outcomes of the project will lead to better diagnostic decisions and will lead to increased efficiency in Australian Industries.Read moreRead less
Effective Techniques and Methodologies for Multi-Database Mining. This project develops a high-performance multi-database mining system. This project is significant because (1) it is imperative due to a great deal of multi-databases widely used in organizations; (2) it is difficult due to essential differences between mono- and multi-databases; (3) existing multi-database mining techniques are inadequate; and (4) the new mining strategies in this project can make a vast improvement of the abilit ....Effective Techniques and Methodologies for Multi-Database Mining. This project develops a high-performance multi-database mining system. This project is significant because (1) it is imperative due to a great deal of multi-databases widely used in organizations; (2) it is difficult due to essential differences between mono- and multi-databases; (3) existing multi-database mining techniques are inadequate; and (4) the new mining strategies in this project can make a vast improvement of the ability and performance of multi-database mining systems. The expected outcomes are: an application-independent database classification, a local instance analysis and a prototype system. These proposed techniques are innovative, effective and efficient in identifying novel patterns from multi-databases.Read moreRead less
Ontology-Based Group Pattern Discovery Systems for Mining Multiple Data Sources. This project will aim at the frontier technologies development for practical techniques in the context of real multiple-data-source mining systems, including stock data and e-business data analysis. It will bring Australian individuals and organizations (i) high quality information from multiple data sources and (ii) automatically pattern discovery systems for tackling the multiple data source problem. This will lea ....Ontology-Based Group Pattern Discovery Systems for Mining Multiple Data Sources. This project will aim at the frontier technologies development for practical techniques in the context of real multiple-data-source mining systems, including stock data and e-business data analysis. It will bring Australian individuals and organizations (i) high quality information from multiple data sources and (ii) automatically pattern discovery systems for tackling the multiple data source problem. This will lead to greatly enhance the international competition of Australian companies and significantly reduce investing risks. 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
Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over ti ....Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over time and captured by different sensors and identify correlations between historic security incidents and current data attacks. This project will significantly help to secure data on cloud for organisations in Australia and benefit fast-growing security sensitive data hosting and applications on cloud.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
Towards High-Order Structure Search on Large-Scale Graphs. High-order structure search over large-scale graphs has many applications including cybersecurity, crime detection, social media, marketing recommendation, and public health. The project aims to lay the scientific foundations and develop novel computing techniques for efficiently conducting structure search. The outcomes include novel computing paradigms, algorithms, indexing, incremental computation, and distributed solutions. The succe ....Towards High-Order Structure Search on Large-Scale Graphs. High-order structure search over large-scale graphs has many applications including cybersecurity, crime detection, social media, marketing recommendation, and public health. The project aims to lay the scientific foundations and develop novel computing techniques for efficiently conducting structure search. The outcomes include novel computing paradigms, algorithms, indexing, incremental computation, and distributed solutions. The success of the project will directly contribute to the scientific foundation of Big Data computation. It will also contribute to the development of local industry involving cybersecurity, social media based recommendation, network management, and E-business.Read moreRead less