Effective Fuzzy Systems for Complex Structured Data Using Fuzzy Signatures. We are developing systematic, heuristic and mathematical techniques to produce effective fuzzy systems for complex structured data. Many or most real world problems have data which has interdependent sub-components depending on the context (eg only female patients need be tested for pregnancy), and often has missing components. Our techniques use fuzzy signatures to extend simple fuzzy systems to deal with data with such ....Effective Fuzzy Systems for Complex Structured Data Using Fuzzy Signatures. We are developing systematic, heuristic and mathematical techniques to produce effective fuzzy systems for complex structured data. Many or most real world problems have data which has interdependent sub-components depending on the context (eg only female patients need be tested for pregnancy), and often has missing components. Our techniques use fuzzy signatures to extend simple fuzzy systems to deal with data with such complex (sub-)structure. This produces effective fuzzy systems with wide applicability to real problems, in telecommunications, and petroleum reservoir data.Read moreRead less
Resource-bounded adaptive inference of accurate conditional probability estimates from data. This project will develop machine learning techniques with a valuable new capability: the ability to produce estimates of complex conditional probabilities to varying levels of expected accuracy depending upon the constraints of available computational resources. This will provide significant competitive advantage to developers of many types of online application by allowing them to maximise utilisation ....Resource-bounded adaptive inference of accurate conditional probability estimates from data. This project will develop machine learning techniques with a valuable new capability: the ability to produce estimates of complex conditional probabilities to varying levels of expected accuracy depending upon the constraints of available computational resources. This will provide significant competitive advantage to developers of many types of online application by allowing them to maximise utilisation of available computational resources when making inferences from data, together with the flexibility to trade-off accuracy and computing resources during system design. Australia will also benefit by strengthening its machine learning expertise, which is central to many complex and intelligent systems and the booming data mining industry.Read moreRead less
Supporting adaptive, interactive documents. The project will improve comprehensibility of technical material, reduce paper usage, encourage collaborative science, improve the reliability of published science (by allowing post-publication annotation and correction), and improve the accessibility of technical material for readers who are blind or have poor vision. The project also holds considerable potential for supporting Australian companies in the publishing and document processing industries.
Multi-Ontologies meet UML: Improving the Software Engineering of Multi-Agent Systems. Multi-agent systems are a new style of software well suited for open, dynamic, distributed, global, heterogeneous environments such as the Internet. Systematic methods are needed to allow multi-agent systems to reason effectively with high level knowledge. This research draws on software engineering practice to develop a theory and methodology for multi-ontologies for expressing knowledge within multi-agent sys ....Multi-Ontologies meet UML: Improving the Software Engineering of Multi-Agent Systems. Multi-agent systems are a new style of software well suited for open, dynamic, distributed, global, heterogeneous environments such as the Internet. Systematic methods are needed to allow multi-agent systems to reason effectively with high level knowledge. This research draws on software engineering practice to develop a theory and methodology for multi-ontologies for expressing knowledge within multi-agent systems that facilitate adaptation and change.
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Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering ap ....Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering applications which will both reduced the bandwidth required and make the internet safer for users. Finally, it will enable rapid deployment of sensor networks for monitoring and detection, such as for environmental monitoring and safeguarding Australia's borders.Read moreRead less
Personalised Content Delivery for Assisted Navigation of Information Rich, Physical Environments such as a Museum. The research will yield improved international standing through scientific advances disseminated through high impact refereed publications and open source software. The collaborations within the project will make Melbourne a hub for research in user modeling and language technology. This will attract post-graduate students in these areas, and potentially commercialisation interest. ....Personalised Content Delivery for Assisted Navigation of Information Rich, Physical Environments such as a Museum. The research will yield improved international standing through scientific advances disseminated through high impact refereed publications and open source software. The collaborations within the project will make Melbourne a hub for research in user modeling and language technology. This will attract post-graduate students in these areas, and potentially commercialisation interest. The demonstration prototypes will provide proof of concept of eventual applications that improve the capabilities of the environments in which we live. These applications, which can be investigated by follow-up projects, will in turn encourage collaborations with Australian companies seeking to build innovative software applications.Read moreRead less
Computational Intelligence Methods for Financial Applications. Complex financial problems can be better addressed with software that can learn from available data and adapt to environmental changes. It is therefore essential to develop technologies that enable prediction and optimisation in constrained and dynamic environments. There are currently some limitations in existing business decision support systems despite their ubiquity providing an opportunity for Australia to be at the forefront as ....Computational Intelligence Methods for Financial Applications. Complex financial problems can be better addressed with software that can learn from available data and adapt to environmental changes. It is therefore essential to develop technologies that enable prediction and optimisation in constrained and dynamic environments. There are currently some limitations in existing business decision support systems despite their ubiquity providing an opportunity for Australia to be at the forefront as new standards in the field are developed. Furthermore, the fund management industry (particularly superannuation) is significant to the Australian economy and development of this technology has the potential to enhance its performance and reputation.Read moreRead less
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.
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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Privacy Preserving Data Mining as Autonomous Data Analysis Expands into Safeguarding from Threats like Crime and Terrorism. In a world characterized by digitally coded data, Data Mining allows automatic exploration of huge numbers of personal records for target marketing, as well as demographic, medical and criminal research. Investigations into terrorist attacks use this technology, but a balance with privacy protection is necessary. Even if names and unique identifiers are removed, computer me ....Privacy Preserving Data Mining as Autonomous Data Analysis Expands into Safeguarding from Threats like Crime and Terrorism. In a world characterized by digitally coded data, Data Mining allows automatic exploration of huge numbers of personal records for target marketing, as well as demographic, medical and criminal research. Investigations into terrorist attacks use this technology, but a balance with privacy protection is necessary. Even if names and unique identifiers are removed, computer methods can be used to infer confidential information about individuals. This project develops new techniques to ensure privacy and alleviate public concerns such as secondary use of personal data. We shall develop new methods for replacing original data with data that exhibits approximately the same patterns, but conceals sensitive data.Read moreRead less