Discovery Early Career Researcher Award - Grant ID: DE230100761
Funder
Australian Research Council
Funding Amount
$430,504.00
Summary
Identifying biases in news using models of narrative framing. This project aims to develop tools to detect biased narratives and one-sided framing in news stories using novel natural language processing methods to understand the text more deeply. Unlike existing methods, which overly rely on surface word co-occurrences patterns, the novel methods will be able to capture narratives in a more holistic and intuitive manner. Expected outcomes include new modeling techniques grounded in theory and a ....Identifying biases in news using models of narrative framing. This project aims to develop tools to detect biased narratives and one-sided framing in news stories using novel natural language processing methods to understand the text more deeply. Unlike existing methods, which overly rely on surface word co-occurrences patterns, the novel methods will be able to capture narratives in a more holistic and intuitive manner. Expected outcomes include new modeling techniques grounded in theory and a tool to highlight biases with recommendations for diverse sets of news articles. By raising awareness to biased news reporting, the project will benefit Australians through more balanced public discourse on global challenges, such as climate change and health pandemics.Read moreRead less
Developing Minimum Message Length and Support Vector Machine methods to predict user behaviour. Predicting and modelling customer behaviour enables considerable savings in the telecommunications industry and elsewhere. The resulting predictive models facilitate identifying novice users, identifying fraud, responding to users' needs, guiding and advising users, and forwarding useful information.
We consider two cutting-edge data mining approaches, Minimum Message Length (developed and led by ....Developing Minimum Message Length and Support Vector Machine methods to predict user behaviour. Predicting and modelling customer behaviour enables considerable savings in the telecommunications industry and elsewhere. The resulting predictive models facilitate identifying novice users, identifying fraud, responding to users' needs, guiding and advising users, and forwarding useful information.
We consider two cutting-edge data mining approaches, Minimum Message Length (developed and led by Monash) and Support Vector Machines, in order to create efficient tailor-made software.
Our software will respond to specific groups of users, and their changes over time, rather than just the average user. Moreover, it will integrate the functionalities of existing individual data mining software.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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Intelligent Structured Knowledge Source Integration via Software Agents. This project aims to use flexible information agents to integrate the World Wide Web with a machine readable ontology, namely a large, consistent collection of common sense knowledge. The best developed ontology in the world is Cyc. Cyc's repository of general purpose knowledge is rich and stable, but has a major limitation in requiring its knowledge to be hand-entered by experts. The outcomes of the project will be increas ....Intelligent Structured Knowledge Source Integration via Software Agents. This project aims to use flexible information agents to integrate the World Wide Web with a machine readable ontology, namely a large, consistent collection of common sense knowledge. The best developed ontology in the world is Cyc. Cyc's repository of general purpose knowledge is rich and stable, but has a major limitation in requiring its knowledge to be hand-entered by experts. The outcomes of the project will be increased functionality for ontologies, to enable expert reasoning programs wishing to use a formal ontology such as Cyc to have access to the wealth of knowledge on the World Wide Web.Read moreRead less
Methods and software for efficiently solving the transportation crewing problem. This project will target major savings in airlines, trucking, rail and public transport, with resulting benefits for industrial logistics, travel and tourism. The results discovered within the project will enable the industrial partner, CTI, to develop solutions for major companies worldwide. The results can also be transferred to other industrial optimisation applications, such as mining, services and manufacturin ....Methods and software for efficiently solving the transportation crewing problem. This project will target major savings in airlines, trucking, rail and public transport, with resulting benefits for industrial logistics, travel and tourism. The results discovered within the project will enable the industrial partner, CTI, to develop solutions for major companies worldwide. The results can also be transferred to other industrial optimisation applications, such as mining, services and manufacturing.
Finally the project will build on Australia's international prominence in data analysis and combinatorial optimisation, and capitalise on a major opportunity for the Australian software industry.Read moreRead less
Human models for accelerated robot learning and human-robot interaction. This project aims to develop novel approaches to teach robots to proficiently interact with humans in a safe and low-cost manner. To achieve this aim, this project will develop novel models from which various human behaviours can be generated and used to train human-robot interaction policies in simulation. Expected outcomes of this project include new computational models of human behaviour built using cognitive science th ....Human models for accelerated robot learning and human-robot interaction. This project aims to develop novel approaches to teach robots to proficiently interact with humans in a safe and low-cost manner. To achieve this aim, this project will develop novel models from which various human behaviours can be generated and used to train human-robot interaction policies in simulation. Expected outcomes of this project include new computational models of human behaviour built using cognitive science theories and limited data and new training schemes for robot learning in simulation. By training robots in simulation with accurate human models, this research will enable fast and safe robot training to support the deployment and adoption of robots in human contexts such as healthcare facilities, homes, and workplaces.Read moreRead less
Non-invasive Detection Of Hypoglycaemia In People With Diabetes Using Brain Wave Activity
Funder
National Health and Medical Research Council
Funding Amount
$330,447.00
Summary
Hypoglycaemia remains a major cause of morbidity and mortality in people with both type 1 diabetes and type 2 diabetes who require insulin therapy. Current treatments for nocturnal hypoglycaemia are usually ineffective. Combining brain wave recording and artificial intelligence, we will identify the changes that precipitate an episode of hypoglycaemia allowing the development of a non-invasive device to prevent or alleviate these fearful and potentially life-threatening events.
Quantitative measurement of Schizophrenia using Electrovestibulography. Schizophrenia was estimated to cost approximately $1.85billion in 2001 (0.3% of GDP and nearly $50k for each of the 37,000 Australians with the illness). Over one third of the cost is borne by sufferers and their carers. Misdiagnosis and incorrect therapy are common. To date quantitative assessment of Schizophrenics has been impossible making this tool potentially invaluable. An accurate diagnostic test could facilitate earl ....Quantitative measurement of Schizophrenia using Electrovestibulography. Schizophrenia was estimated to cost approximately $1.85billion in 2001 (0.3% of GDP and nearly $50k for each of the 37,000 Australians with the illness). Over one third of the cost is borne by sufferers and their carers. Misdiagnosis and incorrect therapy are common. To date quantitative assessment of Schizophrenics has been impossible making this tool potentially invaluable. An accurate diagnostic test could facilitate earlier diagnosis, more accurate treatment plans, and prevention of debilitating psychotic episodes for the sufferer. By being able to monitor drug efficacy the community can benefit by reduced drug costs, confinement times and hastened new drug development. Read moreRead less