Effective Recommendations based on Multi-Source Data. Large-scale data collected from multiple sources such as the Web, sensor networks, academic publications, and social networks provide a new opportunity to exploit useful information for effective and efficient recommendations and decision making. The project will propose a new framework of recommender systems that is based on analysing relationships between different types of objects from multiple data sources. A graph model will be built to ....Effective Recommendations based on Multi-Source Data. Large-scale data collected from multiple sources such as the Web, sensor networks, academic publications, and social networks provide a new opportunity to exploit useful information for effective and efficient recommendations and decision making. The project will propose a new framework of recommender systems that is based on analysing relationships between different types of objects from multiple data sources. A graph model will be built to represent the extracted semantic relationships and novel linkage-analysis based algorithms will be developed for ranking objects. The results from this project will underpin many critical applications such as healthcare.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130101311
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Predicting health status of geriatric patients from user trusted multimedia observations. The information technology developed in this project will provide health care specialists with a better window into the lives of elderly patients. Their behaviour can then be accurately interpreted, potentially leading to earlier recognition of problems and better treatment.
Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop ne ....Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop new privacy-preserving algorithms on EHD database federations, which can provide efficient data access yet block inside attacks. It will significantly improve the data available for medical research, while reducing the cost of EHD system management and providing visualised decision supports to medical staff and the government health resource planners.Read moreRead less
Learning human activities through low cost, unobtrusive RFID technology. A rapidly growing aged population presents many challenges to Australia's health and aged care services. The outcomes of this project will help aging Australians live in their own homes longer, with greater independence and safety by providing an automated, unobtrusive means for health professionals to monitor activity and intervene as required.
Special Research Initiatives - Grant ID: SR0567393
Funder
Australian Research Council
Funding Amount
$100,000.00
Summary
Infrastructure for large-scale data resource sharing between research institutions – an environmental case study. The project creates a federated distributed data infrastructure for research, that encourages data creators to make their data available to other scientists, and encourages users to make use of data available from many sources. The vision is to establish an ICT infrastructure to facilitate a whole-of-environment approach to environmental research. The outcome is a proof-of-concept ....Infrastructure for large-scale data resource sharing between research institutions – an environmental case study. The project creates a federated distributed data infrastructure for research, that encourages data creators to make their data available to other scientists, and encourages users to make use of data available from many sources. The vision is to establish an ICT infrastructure to facilitate a whole-of-environment approach to environmental research. The outcome is a proof-of-concept application based upon a case study of Queensland Environmental Protection Agency’s databases, to gain an in-depth understanding of the complexity, scope and key technological barriers for establishing an ICT infrastructure, to identify where the latest technologies can be used and where the gaps are for these technologies to be used in environmental sciences.Read moreRead less
Harmonized Messaging - A New Foundation for Automated Process Communication. Process communication, especially in web environments is characterized by complex interactions between heterogeneous and autonomous systems within the enterprise and often between trading partners. An overwhelming number of initiatives and proposals are underway to provide solutions for process specification and communication. However, the focus is often on defining APIs rather than the semantics of the underlying messa ....Harmonized Messaging - A New Foundation for Automated Process Communication. Process communication, especially in web environments is characterized by complex interactions between heterogeneous and autonomous systems within the enterprise and often between trading partners. An overwhelming number of initiatives and proposals are underway to provide solutions for process specification and communication. However, the focus is often on defining APIs rather than the semantics of the underlying message exchange. We see a great potential in changing the current messaging infrastructure to suit its new role in facilitating complex, long running interactions for collaborative processes operating in a decentralized environment. This envisaged next generation of messaging technology will extend its ability to support dynamic business processes in a web-centric environment. Providing a level of harmonisation to multiple messages to form a single custom definable backbone of a newly formed message stream, creates a highly challenging new research direction. There is a strong potential that the project outcomes will present a new way of overcoming well understood difficulties in dealing with multiple communicating processes owned by different partners and executing on disparate systems.Read moreRead less
Multi-resolution spatial query processing. The cost of spatial query processing is directly related to spatial data complexity and accuracy. While spatial data is often stored in a database with the highest level of detail available, not all applications require the same level of detail. Recognising the difficulties of multiple representations of spatial data, in this project we propose to use multi-resolution data structures as a new foundation for efficient, application-dependent, on-demand de ....Multi-resolution spatial query processing. The cost of spatial query processing is directly related to spatial data complexity and accuracy. While spatial data is often stored in a database with the highest level of detail available, not all applications require the same level of detail. Recognising the difficulties of multiple representations of spatial data, in this project we propose to use multi-resolution data structures as a new foundation for efficient, application-dependent, on-demand derivation of data at different resolution levels. The systematic approach adopted in this project has the potential to deliver performance improvement that previous algorithm-level-only research cannot match.Read moreRead less
A New Formal Framework for Service Oriented Process Communication. Cross organizational communication in current business environments is highly dynamic, process driven and web centric. The web services paradigm is emerging as a powerful new technology solution to facilitate complex interactions between heterogeneous and autonomous systems within the enterprise and often between trading partners. Although the industry is inundated with initiatives on web services, most are heavily focussed on th ....A New Formal Framework for Service Oriented Process Communication. Cross organizational communication in current business environments is highly dynamic, process driven and web centric. The web services paradigm is emerging as a powerful new technology solution to facilitate complex interactions between heterogeneous and autonomous systems within the enterprise and often between trading partners. Although the industry is inundated with initiatives on web services, most are heavily focussed on the underlying specification platforms and technology components. We see a great need and potential for developing a formal framework for service oriented process communication. The design of such a formal framework is the focus of this project. Project outcomes not only hold great potential to contribute to fundamental research questions in process specification, validation and ontological evaluation, but will also deliver significant impact on related technologies of messaging middleware, integration platforms and workflow management systems.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200101610
Funder
Australian Research Council
Funding Amount
$403,398.00
Summary
Towards Explainable Multi-source Multivariate Time-series Analysis. The aim of this project is to build deep learning models with transparent reasoning behind the results that can be easily interpreted by humans. The research rests on translating pertinent knowledge from multiple sources of complex data containing event sequences into graph form and embedding those knowledge graphs into a sophisticated deep learning model. Such an accomplishment represents the next great advance in machine intel ....Towards Explainable Multi-source Multivariate Time-series Analysis. The aim of this project is to build deep learning models with transparent reasoning behind the results that can be easily interpreted by humans. The research rests on translating pertinent knowledge from multiple sources of complex data containing event sequences into graph form and embedding those knowledge graphs into a sophisticated deep learning model. Such an accomplishment represents the next great advance in machine intelligence and will lay the theoretical foundations for building intelligent analysis tools that truly work in tandem with people. The potential benefits to science, society, and the Australian economy, particularly in finance, sensor technologies, and emergency health services would be appreciable.Read moreRead less
Building crowd sourced data curation processes. This project aims to tackle the growing problem of data curation. The capacity to effectively utilise the increasing number of datasets available to organisations for timely decision making is diminishing, due to onerous data preparation and curation tasks that have to be performed before the data can be consumed by analytics platforms. The project will be a first attempt at using a novel process-oriented approach in micro-task crowdsourcing, and w ....Building crowd sourced data curation processes. This project aims to tackle the growing problem of data curation. The capacity to effectively utilise the increasing number of datasets available to organisations for timely decision making is diminishing, due to onerous data preparation and curation tasks that have to be performed before the data can be consumed by analytics platforms. The project will be a first attempt at using a novel process-oriented approach in micro-task crowdsourcing, and will create new knowledge to harness the full potential of crowd sourced data curation. This is expected to make a significant benefit towards enhanced organisational capacity to accelerate the time-to-value from data analytics projects.Read moreRead less