Techniques for active conceptual modelling and guided data mining for rapid knowledge discovery. Quick, accurate responses to rapidly evolving phenomena are essential. This project will develop a platform able to accept data from a variety of sources in advance of the full definition of the associated conceptual model. The project will facilitate rapid querying and direct manipulation of the mining process allowing fast, user-oriented results.
Normalizing XML Documents. Our work will be of great benefit, both to the research community and to the ICT industry. The project addresses one of the most important problems in XML usage and we expect our results to be published in important international forums, as has our preliminary research on the topic. This will significantly improve Australia's reputation in research in the ICT area. In the longer term, we intend to build commercial software tools based on the results of our research ....Normalizing XML Documents. Our work will be of great benefit, both to the research community and to the ICT industry. The project addresses one of the most important problems in XML usage and we expect our results to be published in important international forums, as has our preliminary research on the topic. This will significantly improve Australia's reputation in research in the ICT area. In the longer term, we intend to build commercial software tools based on the results of our research and this will be of direct benefit to the Australian economy and the Australian ICT industry.Read moreRead less
Towards knowledge discovery from imperfect and evolving data. Information extraction from data is critical, both to analyse and protect consumer data. However, many learning techniques are developed using perfect, static datasets, quite different to messy, ever-changing real-world data. This project aims to develop data analytics techniques that can extract accurate information in complex structures from imperfect/incomplete data that changes over time. Expected outcomes are a prototype tool, te ....Towards knowledge discovery from imperfect and evolving data. Information extraction from data is critical, both to analyse and protect consumer data. However, many learning techniques are developed using perfect, static datasets, quite different to messy, ever-changing real-world data. This project aims to develop data analytics techniques that can extract accurate information in complex structures from imperfect/incomplete data that changes over time. Expected outcomes are a prototype tool, tested on real datasets, that combines new techniques in data modelling, algorithm development, and system design. Likely benefits are enhanced Australia's competence in data science through student training and new, robust data tools relevant to critical sectors such as cybersecurity, healthcare, and defence.Read moreRead less
Integration of Object Behavior in Federated Information Systems. Integration of autonomous object-oriented systems requires the integration
of object structure and object behaviour. Research in federated information
systems has so far mainly addressed integration of object structure. This
project will investigate the integration of object behaviour, especially object
life cycles. A major application area is the integration of business processes,
which is typically required when companies me ....Integration of Object Behavior in Federated Information Systems. Integration of autonomous object-oriented systems requires the integration
of object structure and object behaviour. Research in federated information
systems has so far mainly addressed integration of object structure. This
project will investigate the integration of object behaviour, especially object
life cycles. A major application area is the integration of business processes,
which is typically required when companies merge or enter into
consumer-producer relationships and constitutes a key capability for B2B e-commerce
systems. Consistency criteria for behaviour integration
will be defined and applied in a graphical integration tool that guides the
definition of global behavioural views upon autonomous object-oriented systems.
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Dynamic Semantic Interoperability for Business Processes. The integration of independently developed applications constitutes
one of the major bottlenecks in modern software development in
business, industry, and defense, in particular for a nation such as
Australia that is highly reliant on overseas trade. Technologies that
facilitate the smooth application integration promise significant
savings in software development. By offering automated support task,
this project offers the potenti ....Dynamic Semantic Interoperability for Business Processes. The integration of independently developed applications constitutes
one of the major bottlenecks in modern software development in
business, industry, and defense, in particular for a nation such as
Australia that is highly reliant on overseas trade. Technologies that
facilitate the smooth application integration promise significant
savings in software development. By offering automated support task,
this project offers the potential of significant cost savings, highly
beneficial to any industry with a major ICT component. Lessons learned
from the demonstration prototype can be directly carried over into
commercial tool development. The project strengthens links to high
quality European research laboratories.
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Privacy-Preserving Classification for Big-Data Driven Network Traffic. Protecting sensitive information in large network traffic flows while ensuring data usability for classification emerges as a critical problem of increasing significance. Existing techniques do not work on highly heterogeneous traffic from big-data applications for both privacy protection and classification (such as port-based and load- based methods). This project investigates new theories, methods and techniques for solving ....Privacy-Preserving Classification for Big-Data Driven Network Traffic. Protecting sensitive information in large network traffic flows while ensuring data usability for classification emerges as a critical problem of increasing significance. Existing techniques do not work on highly heterogeneous traffic from big-data applications for both privacy protection and classification (such as port-based and load- based methods). This project investigates new theories, methods and techniques for solving this problem. It proposes to develop a set of effective methods for privacy-preserving data publication through combining randomisation with anonymisation, and for classifying the published data through uncertainty leveraging by probabilistic reasoning and accuracy lifting by inter-flow correlation analysis and active learning.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE180100158
Funder
Australian Research Council
Funding Amount
$348,026.00
Summary
A large-scale distributed experimental facility for the internet of things. This project aims to establish a large-scale, real-world experimental facility for the Internet of Things (IoT), which is currently missing in Australia, as well as in the rest of the world. The project is expected to be an essential instrument to achieve Australia’s leadership on key enabling technologies of the IoT, and to provide Australian research community with a unique platform for large-scale experimentation and ....A large-scale distributed experimental facility for the internet of things. This project aims to establish a large-scale, real-world experimental facility for the Internet of Things (IoT), which is currently missing in Australia, as well as in the rest of the world. The project is expected to be an essential instrument to achieve Australia’s leadership on key enabling technologies of the IoT, and to provide Australian research community with a unique platform for large-scale experimentation and evaluation of IoT technologies and services. The project will also serve as a vehicle for the education and training of Australia’s next generation of scholars and engineers, and contribute to Australia’s scientific visibility.Read moreRead less
Development of a Global Decision Support System towards Virtual Manufacturing. The aim of this research project is to develop a global decision support system (GDSS) in order to assist SMEs to improve their competitiveness in the dynamic global market while providing an industry oriented research training for a high calibre PhD student, who would be a valuable asset to Australia. The GDSS will help SMEs leverage their operations in a global context and to adopt a realistic virtual manufacturing ....Development of a Global Decision Support System towards Virtual Manufacturing. The aim of this research project is to develop a global decision support system (GDSS) in order to assist SMEs to improve their competitiveness in the dynamic global market while providing an industry oriented research training for a high calibre PhD student, who would be a valuable asset to Australia. The GDSS will help SMEs leverage their operations in a global context and to adopt a realistic virtual manufacturing system in the future. The significance of the project includes developing a new methodology and a GDSS to assess virtual manufacturing issues for SMEs and assisting them making timely decisions.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180100950
Funder
Australian Research Council
Funding Amount
$368,446.00
Summary
Building intelligence into online video services by learning user interests. This project aims to build an intelligent video streaming service by characterising users’ view interest patterns and predict user interest changes through learning data from Internet to address the challenge caused by astronomic video population. The outcomes of the project will be of great values for users and our society by intelligently filtering out valueless, harmful, illegal and unwanted videos in advance.
Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical application ....Context and Activity Recognition for Personalised Behaviour Recommendation. The Internet of Things (IoT) together with the rising popularity of smartphones opens a new world for many exciting opportunities. The overall goal of this project is to develop new algorithms and data analytical techniques in an IoT environment that can accurately monitor and analyse personalised daily activities on a continuous, real-time basis. The expected result of this project will support many critical applications such as better wellness tracking and lifestyle-related illness prevention, which will be particularly critical to Australia's aging population. This project will also serve as a vehicle to educate and train Australia’s young scholars and engineers.Read moreRead less