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
Adaptive Key-value Store for Future Extreme Heterogeneous Systems. Safe, lasting storage of data, and efficient access to it, is vital for all aspects of computing, ranging from e-commerce applications, and data-management in governments. For the storage of data, persistent key-value stores are central in modern computing platforms. However, contemporary key-value stores have not been designed for emerging extreme heterogeneous computational systems with future hardware accelerators and storage ....Adaptive Key-value Store for Future Extreme Heterogeneous Systems. Safe, lasting storage of data, and efficient access to it, is vital for all aspects of computing, ranging from e-commerce applications, and data-management in governments. For the storage of data, persistent key-value stores are central in modern computing platforms. However, contemporary key-value stores have not been designed for emerging extreme heterogeneous computational systems with future hardware accelerators and storage capabilities, including graphics processor and flash-based memory. This project will devise an adaptive key-value store framework for heterogeneous systems. Our new framework will adaptively harvest the performance potential of future hardware such that applications can cope with fast-growing data sets.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
A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword ....A data driven paradigm for service-oriented system engineering. This project aims to design and develop a data driven paradigm for service-oriented system engineering that allows system engineers and domain experts in different domains to build software systems easily in order to enable fast technology transfer within and across domain boundaries. This model integrates and automates a suite of efficient approaches for system structure determination, validation and recommendation based on keyword search, subgraph isomorphism and substructure query techniques. This project is expected to significantly accelerate the application of new technologies, for example, big data analytics and Internet of Things, in many of Australia's critical domains such as e-Health, smart cities, and cybersecurity.Read moreRead less
Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over ti ....Secure and efficient data leak prevention on cloud. The leak of sensitive data on cloud not only poses serious threats to both public and private organisations but also puts their employees and clients at risk, e.g., economic loss and social impact. The aim of this project is to develop a secure and efficient solution that can detect and prevent leak of data in real-time. Uniquely, the proposed research will develop novel techniques that can monitor data leak security incidents happening over time and captured by different sensors and identify correlations between historic security incidents and current data attacks. This project will significantly help to secure data on cloud for organisations in Australia and benefit fast-growing security sensitive data hosting and applications on cloud.Read moreRead less
Decentralised Collaborative Predictive Analytics on Personal Smart Devices. This project tackles the challenging problem of personalised predictive analytics with resource-constrained personal devices and massive-scale data. The knowledge to be generated concerns privacy, fairness, and resource efficiency in the era of Internet of Things. The expected outcomes include a collaborative learning paradigm for building personalised models on personal smart devices in open and fully decentralised sett ....Decentralised Collaborative Predictive Analytics on Personal Smart Devices. This project tackles the challenging problem of personalised predictive analytics with resource-constrained personal devices and massive-scale data. The knowledge to be generated concerns privacy, fairness, and resource efficiency in the era of Internet of Things. The expected outcomes include a collaborative learning paradigm for building personalised models on personal smart devices in open and fully decentralised settings. Privacy and model fairness are core tenets of the paradigm. Personalised predictive analytics is frontier research that will position Australia at the forefront of AI and give business the tools needed to deploy innovative business systems for market exploitation with a secure, equitable and competitive advantage.Read moreRead less
Real-time Analytics on Urban Trajectory Data for Road Traffic Management. This project aims to develop real-time analytics and data management capabilities that leverage large-scale urban trajectory data to provide road operators with real-time insights into population movements and enable data-driven, customer-centric network operations. Current traffic management practices rely heavily on aggregate vehicle count data from fixed road sensors, which have limitations in accurately measuring traff ....Real-time Analytics on Urban Trajectory Data for Road Traffic Management. This project aims to develop real-time analytics and data management capabilities that leverage large-scale urban trajectory data to provide road operators with real-time insights into population movements and enable data-driven, customer-centric network operations. Current traffic management practices rely heavily on aggregate vehicle count data from fixed road sensors, which have limitations in accurately measuring traffic demand and network congestion propagation. This project seeks to develop innovative technologies to use a wide variety of data sources, especially massive trajectories of vehicles moving across the network, to better understand people's travel demands and road usage patterns and thus better manage the transport system.
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Developing an effective defence to cyber-reputation manipulation attacks. This project will develop new technologies for businesses to accurately identify fake internet reviews. Fake reviews, paid for and/or written with malicious intent, can cause irreparable damage to businesses resulting in revenue loss, consumer dissatisfaction or even closure of businesses. However they are difficult to identify, as they continuously evolve to avoid detection and the volume of Internet reviews makes analysi ....Developing an effective defence to cyber-reputation manipulation attacks. This project will develop new technologies for businesses to accurately identify fake internet reviews. Fake reviews, paid for and/or written with malicious intent, can cause irreparable damage to businesses resulting in revenue loss, consumer dissatisfaction or even closure of businesses. However they are difficult to identify, as they continuously evolve to avoid detection and the volume of Internet reviews makes analysis a monumental task. This project will provide advanced tools to detect fake website reviews and a cybersecurity system prototype ready to be used by industry, making Australia a leader in this field and resulting in a safer internet environment for all.Read moreRead less
Making Spatiotemporal Data More Useful: An Entity Linking Approach. This project aims to establish a methodology for spatiotemporal entity linking by utilising object movement traces to support database integration and data quality management for the next-generation of data where spatiotemporal attributes are ubiquitous. It expects to develop a novel entity linking paradigm for automatic, efficient and reliable spatiotemporal data integration together with a new data privacy study in this contex ....Making Spatiotemporal Data More Useful: An Entity Linking Approach. This project aims to establish a methodology for spatiotemporal entity linking by utilising object movement traces to support database integration and data quality management for the next-generation of data where spatiotemporal attributes are ubiquitous. It expects to develop a novel entity linking paradigm for automatic, efficient and reliable spatiotemporal data integration together with a new data privacy study in this context. Expected outcome include new database technologies for data signature generation and similarity-based search, and improved location data privacy protection methods. This project should provide significant benefits to all areas where high quality spatiotemporal data fusion is essential to meaningful data analysis.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100160
Funder
Australian Research Council
Funding Amount
$423,000.00
Summary
Information Extraction from Large-scale Low-quality Data. Information extraction which identifies entities and relations from data is a key technology that lays the foundation for understanding the semantics of data. This project aims to investigate the problem of information extraction by innovatively exploring the informality and temporal evolution of data. It expects to develop novel techniques for reliable, efficient, and scalable information discovery from large-scale low-quality data. Expe ....Information Extraction from Large-scale Low-quality Data. Information extraction which identifies entities and relations from data is a key technology that lays the foundation for understanding the semantics of data. This project aims to investigate the problem of information extraction by innovatively exploring the informality and temporal evolution of data. It expects to develop novel techniques for reliable, efficient, and scalable information discovery from large-scale low-quality data. Expected outcomes include a set of collective, contextualised, and temporal-aware algorithms for information extraction and integration, built on top of effective indexing and in-parallel processing. This project is anticipated to benefit a considerable number of data-driven intelligence-based applications.Read moreRead less