Reputation-based Trust Framework for Composed Services. This project aims at providing a uniform and efficient framework for bootstrapping, establishing, and propagating reputation in composed Web services. Reputation is used as a key criterion for establishing trust among composed Web services. Web services are de-facto the technology of choice for the deployment of an increasing number of Web-based solutions for such emerging applications as cloud computing. Because of the distributed and dece ....Reputation-based Trust Framework for Composed Services. This project aims at providing a uniform and efficient framework for bootstrapping, establishing, and propagating reputation in composed Web services. Reputation is used as a key criterion for establishing trust among composed Web services. Web services are de-facto the technology of choice for the deployment of an increasing number of Web-based solutions for such emerging applications as cloud computing. Because of the distributed and decentralised nature of the Web, there is a need to establish a trust framework for selecting and composing Web services. The key parameter will be based on Web service reputation in delivering services.Read moreRead less
Contextual Behabiour Predictions in Dynamic Mobile E-commerce. The project aims to address behaviour prediction and develop novel techniques and tools for modelling, predicting human behaviours and making effective recommendations based on ubiquitous user behaviour data in mobile e-commerce. The techniques enable multi-source data fusion, context learning and model adaptation, and dynamic recommendation with interpretability ability. Expected outcomes include advances in data analytics theory an ....Contextual Behabiour Predictions in Dynamic Mobile E-commerce. The project aims to address behaviour prediction and develop novel techniques and tools for modelling, predicting human behaviours and making effective recommendations based on ubiquitous user behaviour data in mobile e-commerce. The techniques enable multi-source data fusion, context learning and model adaptation, and dynamic recommendation with interpretability ability. Expected outcomes include advances in data analytics theory and informed decision-making. This provides significant benefits of not only placing Australia in the forefront of exploiting multimodal user behaviour big data in dynamic e-commerce but also transforming Australian government and businesses to intelligent and contextual services adaptive to complex situations.Read moreRead less
Broadening Choice and Increasing Diversity in Public Schools. Currently, most families are limited to the public school in their catchment area, meaning the area in which they can afford to live. This leads to socio-economically and ethnically homogenous schools and entrenches disadvantage, as well as denying students the crucial life lessons that flow from being part of a diverse student body. This project aims to investigate a model for allocating public school places that integrates catchment ....Broadening Choice and Increasing Diversity in Public Schools. Currently, most families are limited to the public school in their catchment area, meaning the area in which they can afford to live. This leads to socio-economically and ethnically homogenous schools and entrenches disadvantage, as well as denying students the crucial life lessons that flow from being part of a diverse student body. This project aims to investigate a model for allocating public school places that integrates catchment areas. The expected outcome would be a system that gives families a wider choice, enabling them to enrol in out-of-area schools, while ensuring that allocations remain fair, equitable and balanced, and also delivering benefits such as achieving a desired level of diversity in student populations within schoolsRead moreRead less
Leveraging open innovation: software and processes for engaging with online communities. The research could help transform the ability of Australian industry to design software systems and processes that (i) engage with online communities to create and enhance organizational knowledge, (ii) accelerate innovation processes, and (iii) exploit existing intellectual property (IP).
Adaptive and Ubiquitous Trust Framework for Internet of Things interactions. The aim of the project is to address the Trust challenges in Internet of Things (IoT) environments, thus enabling the wide deployment of potentially billions of IoT devices. This project will generate new knowledge in the area of IoT Trust by developing novel techniques to establish trust in highly dynamic crowdsourcing IoT environments. The project's main outcomes include the development of a ubiquitous and adaptive mu ....Adaptive and Ubiquitous Trust Framework for Internet of Things interactions. The aim of the project is to address the Trust challenges in Internet of Things (IoT) environments, thus enabling the wide deployment of potentially billions of IoT devices. This project will generate new knowledge in the area of IoT Trust by developing novel techniques to establish trust in highly dynamic crowdsourcing IoT environments. The project's main outcomes include the development of a ubiquitous and adaptive multi-component trust framework reflecting trust perspectives. The developed solutions will allow the establishment of trusted interactions among crowdsourced IoT devices and wider deployment of convenient and just-in-time services, thus enabling the development of novel applications, such as the crowdsourcing of green energy.Read moreRead less
Testing strategy-proofness in matching markets: an experimental study. This project seeks to test and improve matching algorithms by investigating the effect of advice on strategy-proofness. Matching algorithms are used to solve allocation problems in designed markets (eg school or house allocation problems). Many of the algorithms employed are strategy-proof: participants never gain from strategising, that is, from lying about their preferences. Strategy-proofness had been seemingly validated b ....Testing strategy-proofness in matching markets: an experimental study. This project seeks to test and improve matching algorithms by investigating the effect of advice on strategy-proofness. Matching algorithms are used to solve allocation problems in designed markets (eg school or house allocation problems). Many of the algorithms employed are strategy-proof: participants never gain from strategising, that is, from lying about their preferences. Strategy-proofness had been seemingly validated by experimental research, but new evidence suggests that participants could be prone to follow wrong advice and therefore lie. In order to improve the performance of designed markets, the project proposes to further test strategy-proofness by investigating how advice can affect truth-telling in strategy-proof algorithms and whether learning can counteract or complement the effect of advice.Read moreRead less
Long-term Cloud Service Composition. This project proposes an economic model-based framework for the selection and composition of cloud services, thus creating an efficient market for cloud consumers and providers. The project will use economic models that incorporate a range of quality of service (QoS) parameters as a key driver for optimising the selection of cloud services and the acceptance of consumer requests. The main outcomes of this project aim to increase efficiencies in the cloud mark ....Long-term Cloud Service Composition. This project proposes an economic model-based framework for the selection and composition of cloud services, thus creating an efficient market for cloud consumers and providers. The project will use economic models that incorporate a range of quality of service (QoS) parameters as a key driver for optimising the selection of cloud services and the acceptance of consumer requests. The main outcomes of this project aim to increase efficiencies in the cloud market, benefiting consumers and providers.Read moreRead less
What Can You Trust in the Large and Noisy Web? This project will develop innovative techniques to efficiently and effectively distill truthful information from the inherently unreliable and large-scale Web environment, where misinformation has been widely regarded as a grand challenge for the next decade. The results of this project will not only maintain Australia’s leadership in this frontier research area, but also support many important applications that safeguard Australian people and econo ....What Can You Trust in the Large and Noisy Web? This project will develop innovative techniques to efficiently and effectively distill truthful information from the inherently unreliable and large-scale Web environment, where misinformation has been widely regarded as a grand challenge for the next decade. The results of this project will not only maintain Australia’s leadership in this frontier research area, but also support many important applications that safeguard Australian people and economy such as emergency and disaster management and online healthcare. This project also serves as an excellent vehicle for the education and training of Australia’s next generation of scholars and engineers.Read moreRead less
Reputation-based trust management in crowdsourcing environments. This project aims to address the critical need for enabling trustworthy crowd sourcing environments. Expected outcomes include innovative solutions to evaluate the reputation and expertise portfolio of workers and identify malicious workers, with the ultimate goal of making personalised recommendations of trustworthy workers with expertise to the requesters who have published tasks. This project is expected to provide key solutions ....Reputation-based trust management in crowdsourcing environments. This project aims to address the critical need for enabling trustworthy crowd sourcing environments. Expected outcomes include innovative solutions to evaluate the reputation and expertise portfolio of workers and identify malicious workers, with the ultimate goal of making personalised recommendations of trustworthy workers with expertise to the requesters who have published tasks. This project is expected to provide key solutions to globally leading crowd sourcing platforms originating in Australia and benefit Australian and worldwide Internet users.Read moreRead less
The effect of competition and doctor heterogeneity on prices charged by doctors. Prices charged by doctors can have important effects on health care costs, access to health care and health status. This research will examine the determinants of prices charged by doctors. The results will be important in understanding the pricing practices of doctors and their impact on health care costs.