Reconceiving Machine Learning. The proposed research will develop a new way to consider problems to which machine learning can be applied. Machine learning is crucial enabler of the digital economy. The research will provide better opportunities for Australian industry to gain a competitive advantage with machine learning technology. The framework developed will enable better opportunities for collaborative research and will build and strengthen international linkages.
Web Services Reputation Management. This project directly supports the National Research Priority 4: Safeguarding Australia. More specifically, it aims at creating mechanisms that will make it more difficult to use the Internet as a platform for launching attacks against the business processes of Australian organisations that provide and consume Web services. At the same time this will stimulate the establishment of high quality WS markets. As direct social benefit of this research, Australian o ....Web Services Reputation Management. This project directly supports the National Research Priority 4: Safeguarding Australia. More specifically, it aims at creating mechanisms that will make it more difficult to use the Internet as a platform for launching attacks against the business processes of Australian organisations that provide and consume Web services. At the same time this will stimulate the establishment of high quality WS markets. As direct social benefit of this research, Australian organisations will be able to integrate the best quality Web services as part of their business processes, and thereby avoid being negatively impacted by low quality and deceptive Web services. Read moreRead less
Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected ....Kernel and Margin Based Machine Learning Algorithms. Certain machine learning algorithms, such as support vector machines, utilizing
the ideas of large margins and kernels have attracted much attention lately
because of their impressive performance on real world problems such as optical
character recognition. We plan to refine and extend such algorithms to a wide
range of different machine learning problems such as gene sequence analysis,
image processing and text classification. Expected outcomes include the
development of software that allows the solution of hitherto unsolved machine
learning problems, and the ability to solve problems larger than those solvable
by the current generation of machine learning tools.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100235
Funder
Australian Research Council
Funding Amount
$280,000.00
Summary
Accelerating Australia's large scale video surveillance research programmes. The research to be conducted using this infrastructure will bring immense benefits to Australia in terms of increased levels of public safety and in the protection of critical facilities from terrorism and other crimes, by developing better surveillance systems. This will provide both increases in measurable research outputs and opportunities for Australian business to commercialise these systems. The infrastructure wil ....Accelerating Australia's large scale video surveillance research programmes. The research to be conducted using this infrastructure will bring immense benefits to Australia in terms of increased levels of public safety and in the protection of critical facilities from terrorism and other crimes, by developing better surveillance systems. This will provide both increases in measurable research outputs and opportunities for Australian business to commercialise these systems. The infrastructure will accelerate the pace of surveillance research and development in Australia, enhancing the competitiveness of both Australia's researchers and the businesses that will commercialise these researchers' discoveries.Read moreRead less
Discovering Activity Patterns Driven by High Impacts in Heterogeneous and Imbalanced Data. The identification of high impact activities is important for detecting and preventing their occurrences and reducing resulting risks and losses to our society. This project will deliver cutting-edge techniques for effectively extracting activity patterns driven by high business impacts. It can safeguard Australia and build and transform Australian industries by delivering frontier techniques and smart pre ....Discovering Activity Patterns Driven by High Impacts in Heterogeneous and Imbalanced Data. The identification of high impact activities is important for detecting and preventing their occurrences and reducing resulting risks and losses to our society. This project will deliver cutting-edge techniques for effectively extracting activity patterns driven by high business impacts. It can safeguard Australia and build and transform Australian industries by delivering frontier techniques and smart prevention and intervention capabilities to enhance key industries such as finance compliance, national security and crime reduction. The resulting activity mining system, researchers trained and high quality publications will further enhance Australia's global leading role in tackling critical data mining challenges and applications.Read moreRead less
Developing optimal synthesis strategies in distributed expert systems. The aim of this project is to investigate synthesis strategies in distributed expert systems (DESs). Such strategies are used to synthesize multiple solutions to the same task from different experts (either human experts or expert systerms) in order to obtain the final solution to the task. These strategies could be used in a wide application of domains such as insurance agencies and medical diagnosis systems. The expected ....Developing optimal synthesis strategies in distributed expert systems. The aim of this project is to investigate synthesis strategies in distributed expert systems (DESs). Such strategies are used to synthesize multiple solutions to the same task from different experts (either human experts or expert systerms) in order to obtain the final solution to the task. These strategies could be used in a wide application of domains such as insurance agencies and medical diagnosis systems. The expected outcomes are to develop computational strategies, neural network strategies, and case-based strategies for solving different synthesis cases.Read moreRead less
A scalable and portable question-answering system. The current availability of large volumes of free text digitally stored demands the development of methodologies that can automatically find specific answers to user questions about this "unstructured" information. The goal of this project is to develop a scalable portable and domain-independent real-time natural-language question-answering system that explores the logical contents of the text. To achieve this we will fuse current approaches to ....A scalable and portable question-answering system. The current availability of large volumes of free text digitally stored demands the development of methodologies that can automatically find specific answers to user questions about this "unstructured" information. The goal of this project is to develop a scalable portable and domain-independent real-time natural-language question-answering system that explores the logical contents of the text. To achieve this we will fuse current approaches to question answering with approaches that look at the logical contents of the questions and answer candidates. A central part of the project will be the characterisation of the optimal logical forms, the determination of efficient methods to create and store sentence logical forms of potentially large volumes of text, and the treatment of difficult questions by incorporating summarisation and text generation techniques.Read moreRead less
A Layered Controlled Natural Language for Knowledge Representation. In this research project we will develop a controlled natural language for knowledge representation that has the potential to bridge the gap between fragments of natural language and formal languages. This controlled language will be based on a variety of increasing sophisticated layers, each building upon those below it by providing enhancements in expressive power. Sentences of the controlled language will be unambiguously tra ....A Layered Controlled Natural Language for Knowledge Representation. In this research project we will develop a controlled natural language for knowledge representation that has the potential to bridge the gap between fragments of natural language and formal languages. This controlled language will be based on a variety of increasing sophisticated layers, each building upon those below it by providing enhancements in expressive power. Sentences of the controlled language will be unambiguously translatable into a corresponding formal language. Anyone who can read and write English can immediately use the controlled language with the help an intelligent text editor. This technology will make it possible for non-specialists to write problem specifications in terms of the application domain without the need to formally encode the information.Read moreRead less
Integrating deep-earth and surface processes for frontier-basin exploration. It is well-known that mantle convection has a profound influence on basin evolution, and the next step will be to quantify this relationship and provide the science that will make these concepts applicable to exploration. To do this, we will develop a workflow to link plate-reconstruction software with the mantle convection modelling to link plate motions mantle convection and the history of sedimentation systematically ....Integrating deep-earth and surface processes for frontier-basin exploration. It is well-known that mantle convection has a profound influence on basin evolution, and the next step will be to quantify this relationship and provide the science that will make these concepts applicable to exploration. To do this, we will develop a workflow to link plate-reconstruction software with the mantle convection modelling to link plate motions mantle convection and the history of sedimentation systematically for the first time for frontier basin-scale applications. We will apply these emerging technologies to the evolution of basins in the Arctic borderlands frontier for resource exploration and on the Australian continent.Read moreRead less
Classification and Prediction Modelling for Financial Distress, Tax Debt and Insolvency for ATO Clients. The Australian Taxation Office (ATO) has clients who are not able to meet their taxation debts, resulting in revenue shortfalls for both the State and Federal Governments. Through this project, we will develop predictive models and techniques which identify client classes and clusters in the ATO client population and the defining attributes of these collections - especially those which are a ....Classification and Prediction Modelling for Financial Distress, Tax Debt and Insolvency for ATO Clients. The Australian Taxation Office (ATO) has clients who are not able to meet their taxation debts, resulting in revenue shortfalls for both the State and Federal Governments. Through this project, we will develop predictive models and techniques which identify client classes and clusters in the ATO client population and the defining attributes of these collections - especially those which are at high risk of incurring debt and defaulting on paying taxes. In turn, the early identification of clients in financial distress will allow the ATO to give them assistance so that they can reduce their debts and meet their financial obligations.Read moreRead less