Digital nomadism: How IT enables new forms of working and organising. This project aims to gain a better understanding of digital nomadism. Digital nomads use IT platforms to work remotely over the Internet while perpetually travelling. The project will develop new knowledge by better understanding of how IT transforms work and enable digital nomadism, the motivations and values of workers and their clients/organisations engaged in digital nomadism and the implications and consequences of digita ....Digital nomadism: How IT enables new forms of working and organising. This project aims to gain a better understanding of digital nomadism. Digital nomads use IT platforms to work remotely over the Internet while perpetually travelling. The project will develop new knowledge by better understanding of how IT transforms work and enable digital nomadism, the motivations and values of workers and their clients/organisations engaged in digital nomadism and the implications and consequences of digital nomadism for workers and clients/organisations. The project is expected to have a significant impact on policy and public discourse by providing an in-depth explanation and understanding of digital nomadism based on rigorous research.Read moreRead less
Enhancing privacy preserving in dynamic cyberspace. This project aims to develop a novel infrastructure operational monitoring and management strategy to reduce the redundant maintenance actions and achieve a cost-effective approach for civil infrastructure asset management. The project will use multiple social networks as a platform for the project, with the potential for the results to be extended to any dynamic cyberspace. Project outcomes will include a set of new analysis theories and tools ....Enhancing privacy preserving in dynamic cyberspace. This project aims to develop a novel infrastructure operational monitoring and management strategy to reduce the redundant maintenance actions and achieve a cost-effective approach for civil infrastructure asset management. The project will use multiple social networks as a platform for the project, with the potential for the results to be extended to any dynamic cyberspace. Project outcomes will include a set of new analysis theories and tools to facilitate government, companies, individuals, and organisations to enhance their information gathering and privacy-preserving capabilities. This is expected to enhance the credibility of the government and organisations and save the possible financial loss of companies and individuals.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
Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human expl ....Robust Preference Inference from Spatial-Temporal Interaction Networks. This project aims to develop innovative techniques for effectively and efficiently managing user preference profiles from less labelled, sparse and noisy interaction data. A unified novel learning framework along with a set of data analysis techniques are expected to be developed from this project, which will provide a non-intrusive way of conducting predictive analysis on user preference profiling via discovering human explicit and implicit interest domains. The expected results of this application 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 cyber security, healthcare, and e-Commerce.Read moreRead less
Next Generation Spatial Data Management for Virtual Spatial Systems. This project aims to design novel spatial data retrieval methods for efficient and accurate querying of large datasets with location information. Spatial data is being generated at an unprecedented rate due to the prevalence of mobile devices and ubiquitous connectivity. However, harnessing this data is hampered by outdated and inefficient methods. The project will investigate data retrieval methods that self-optimise for high ....Next Generation Spatial Data Management for Virtual Spatial Systems. This project aims to design novel spatial data retrieval methods for efficient and accurate querying of large datasets with location information. Spatial data is being generated at an unprecedented rate due to the prevalence of mobile devices and ubiquitous connectivity. However, harnessing this data is hampered by outdated and inefficient methods. The project will investigate data retrieval methods that self-optimise for high query efficiency and accuracy, by utilising underlying real-world data patterns. It will enable novel applications for virtual spatial systems with large-scale querying needs, such as spatial digital twins and metaverses, benefiting location-based service providers, urban planners, and emergency management agencies.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
The right to be forgotten: GDPR modelling in cross-domain social networks . The project aims to develop a theoretical model and practical mechanisms to address the critical challenge – ‘right to be forgotten’ - raised from the General Data Protection Regulation (GDPR) with minimal compromising of the utility of the data. To achieve the aim, we will design a ‘right to be forgotten’ framework and associated erasure mechanisms that are effective even information is derived from multiple related soc ....The right to be forgotten: GDPR modelling in cross-domain social networks . The project aims to develop a theoretical model and practical mechanisms to address the critical challenge – ‘right to be forgotten’ - raised from the General Data Protection Regulation (GDPR) with minimal compromising of the utility of the data. To achieve the aim, we will design a ‘right to be forgotten’ framework and associated erasure mechanisms that are effective even information is derived from multiple related social networks. The framework will be created by identifying heterogeneous information, modelling individual behaviour patterns and designing erasure policies. The outcomes of the project can be used by the government to provide privacy guarantees to Australian cyberspace and by industry to protect their clients’ privacy.Read moreRead less
Efficient and Scalable Similarity Query Processing on Big Streaming Graphs . This project aims to develop novel approaches for efficient and scalable similarity queries on big streaming graphs which are large-scale graphs where graph nodes and edges may arrive or expire at high speed. Three key challenges are expected to be addressed including high speed, large variety, and big volume of streaming graphs. Expected outcomes include new theories, novel indexing and query processing techniques, an ....Efficient and Scalable Similarity Query Processing on Big Streaming Graphs . This project aims to develop novel approaches for efficient and scalable similarity queries on big streaming graphs which are large-scale graphs where graph nodes and edges may arrive or expire at high speed. Three key challenges are expected to be addressed including high speed, large variety, and big volume of streaming graphs. Expected outcomes include new theories, novel indexing and query processing techniques, and advanced distributed algorithms as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications, such as e-commerce, cybersecurity, health, social networks, and bio-informatics.
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Trust and Safety in Autonomous Mobility Systems: A Human-centred Approach. This project aims to understand the link between trust, safety, and the public acceptance of driverless cars. The uptake of autonomous mobility systems relies upon public trust. Recent injuries, and even a fatality, have highlighted the risks they pose to pedestrians in particular. The project investigates new interfaces for improving public trust and pedestrial safety by allowing vehicles to communicate with the people a ....Trust and Safety in Autonomous Mobility Systems: A Human-centred Approach. This project aims to understand the link between trust, safety, and the public acceptance of driverless cars. The uptake of autonomous mobility systems relies upon public trust. Recent injuries, and even a fatality, have highlighted the risks they pose to pedestrians in particular. The project investigates new interfaces for improving public trust and pedestrial safety by allowing vehicles to communicate with the people around them. Along the way, it develops a validated approach for simulating real interactions with autonomous vehicles in a virtual-reality environment. Benefits include strategies for making driverless cars safer for pedestrians and a new approach for testing solutions to this emerging problem in a low-cost, low-risk way.Read moreRead less
Effective and Efficient Data Quality Management for Data Lakes. This project aims to enhance the quality and completeness for data in data lakes by innovative and judicious use of Database and Artificial Intelligence techniques. To achieve the aim, we will develop knowledge-enhanced error correction during data ingestion, flexible and efficient data exploration, and heterogeneity-tolerant scalable data integration solutions. Its significance lies in integrating techniques from both database and ....Effective and Efficient Data Quality Management for Data Lakes. This project aims to enhance the quality and completeness for data in data lakes by innovative and judicious use of Database and Artificial Intelligence techniques. To achieve the aim, we will develop knowledge-enhanced error correction during data ingestion, flexible and efficient data exploration, and heterogeneity-tolerant scalable data integration solutions. Its significance lies in integrating techniques from both database and artificial intelligence areas to deliver effective solutions for challenging problems in data lakes. The outcome of this project will provide new knowledge in this cutting-edge domain, and provide additional value and immediate benefits to all applications built upon data lakes. Read moreRead less