Stream Data Classification in the Age of 5G Networks. This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a sys ....Stream Data Classification in the Age of 5G Networks. This project aims to develop a novel stream data classification model to handle the challenges in the era of 5G networks, such as the scope of the stream data, the complexity of their relationship, the diversity of contained information and the incorrect readings of numerous sensors. The project addresses a significant knowledge gap by exploring and modelling the stronger correlation between data instances in the streams. The outcome is a system that is highly efficient, accurate and corrupted-data-tolerant classification solutions for individual stream data as well as multiple stream data. The expected benefits will be far-ranging and adaptable to many domains, such as smart home, medical and healthcare, transportation and manufacturing. Read moreRead less
Continuous intent tracking for virtual assistance using big contextual data. Recently launched Virtual Assistant products such as Amazon Echo and Google Home are commanded by voice and can call apps to do simple tasks like setting timers and playing music. The next-generation virtual assistants will recommend things to be done proactively rather than waiting for commands passively. This project aims to develop algorithms that can predict what a user intends to do and therefore help virtual assis ....Continuous intent tracking for virtual assistance using big contextual data. Recently launched Virtual Assistant products such as Amazon Echo and Google Home are commanded by voice and can call apps to do simple tasks like setting timers and playing music. The next-generation virtual assistants will recommend things to be done proactively rather than waiting for commands passively. This project aims to develop algorithms that can predict what a user intends to do and therefore help virtual assistants make recommendations that suit users’ needs accurately. It will benefit many service industry sectors of Australia by enabling virtual assistants to provide services proactively.Read moreRead less
On effectively modelling and efficiently discovering communities from large networks. Finding and maintaining close communities from very large scale, dynamically changing networks is interesting and challenging. This project aims to develop new techniques to identify such communities as fast as possible through exploiting the rich semantics and individual relationships within the communities.
Personalised Online Learning Analytics by Exploring Multilayer Graph Data . Learning analytics is becoming a significant factor in reducing the drop-out rate of students in online learning. The aim of this project is to develop a reliable, robust, real-time analysis system that automatically reveals multilayered relationships, evaluates students' learning performance, and generates a personal study plan through discovery. This project includes the design of novel algorithms for multilayer graph ....Personalised Online Learning Analytics by Exploring Multilayer Graph Data . Learning analytics is becoming a significant factor in reducing the drop-out rate of students in online learning. The aim of this project is to develop a reliable, robust, real-time analysis system that automatically reveals multilayered relationships, evaluates students' learning performance, and generates a personal study plan through discovery. This project includes the design of novel algorithms for multilayer graph processing, pattern recognition in learning activities, learning performance assessment, and personalised study plan recommendations. The success of this project will significantly enhance the success of online education both in Australia and worldwide and; hence, will save time, money and resources for end users.Read moreRead less
Efficient spatial data management for enabling true ride-sharing. This data management project aims to examine ride-sharing as a model of a complex decision system that can be optimised to deliver better outcomes. Popular ride-sharing apps have quickly evolved into ride-sourcing services that are comparable to calling a taxi on a mobile phone. Such arrangements miss many of the key benefits of true ride-sharing for the society. The project will model incentives by helping people agree on points ....Efficient spatial data management for enabling true ride-sharing. This data management project aims to examine ride-sharing as a model of a complex decision system that can be optimised to deliver better outcomes. Popular ride-sharing apps have quickly evolved into ride-sourcing services that are comparable to calling a taxi on a mobile phone. Such arrangements miss many of the key benefits of true ride-sharing for the society. The project will model incentives by helping people agree on points of interest rather than directly seeking trips from others to set destinations. It also aims to introduce privacy-aware dynamic matching of sharers, and expand to transportation at large, to generate new shared transportation services. The expected outcome of this project is to elevate today's taxi-like ride-sharing services to true ride-sharing arrangements. This is expected to provide benefits such as reduced traffic and emissions, as well as addressing parking issues and other traffic problems.Read moreRead less
Next generation data mining techniques for analysing large evolving networks. In order to understand complex systems such as the Internet or gene interactions, we need to analyse how the networks in these systems function and evolve. This project will provide new methods for extracting knowledge from large network databases so that scientists can learn about the operation of these complex systems.
Multi source inference from heterogeneous dynamic networks. Sophisticated big data applications in engineering, the social sciences and biology are now generating flows of data across multiple sources possessing a variety of structures. An emerging challenge is how to develop data mining methods that can cope with this complexity and diversity to make inferences and provide practical insights. This project will develop methods in tensor data mining that provide a new foundation for extracting us ....Multi source inference from heterogeneous dynamic networks. Sophisticated big data applications in engineering, the social sciences and biology are now generating flows of data across multiple sources possessing a variety of structures. An emerging challenge is how to develop data mining methods that can cope with this complexity and diversity to make inferences and provide practical insights. This project will develop methods in tensor data mining that provide a new foundation for extracting useful knowledge from multi source heterogeneous data sets. This will help accelerate discoveries in the next generation of data driven science.Read moreRead less
Personalised data analytics for the Internet of Me. This project aims to develop data mining methods for extracting comprehensive personalised knowledge, without breaching trust. The Internet of Things will lead to the Internet of Me. Billions of smart devices connected to the Internet record people’s lives. Companies wish to provide highly personalised services that engage their customers, while individuals wish to understand their health, lifestyle, education and personal performance. The chal ....Personalised data analytics for the Internet of Me. This project aims to develop data mining methods for extracting comprehensive personalised knowledge, without breaching trust. The Internet of Things will lead to the Internet of Me. Billions of smart devices connected to the Internet record people’s lives. Companies wish to provide highly personalised services that engage their customers, while individuals wish to understand their health, lifestyle, education and personal performance. The challenge is to analyse individuals’ personal data, and discover how they differentiate from and overlap with others’. This project expects to enable businesses to deepen customer satisfaction and individuals to better understand their personal place in a connected world.Read moreRead less
Real-time and self-adaptive stream data analyser for intensive care management. The clinical benefit of this project will be in improved success rates and reduced mortality and risk in surgery and intensive care units. The Information and communication technology (ICT) benefit of this project is associated with the novel online algorithms and models aligned with the stream data research, and will be enhanced by our stream compression techniques. The stream data analyser developed in this projec ....Real-time and self-adaptive stream data analyser for intensive care management. The clinical benefit of this project will be in improved success rates and reduced mortality and risk in surgery and intensive care units. The Information and communication technology (ICT) benefit of this project is associated with the novel online algorithms and models aligned with the stream data research, and will be enhanced by our stream compression techniques. The stream data analyser developed in this project will be suitable for more than medical surveillance data; it will also improve the processing of other kinds of massive stream data (for example data from remote sensors, communication networks and other dynamic environments). The project involves a scientifically rich collaboration that will enhance the skills of PhD students and staff and drive the field forward.Read moreRead less