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.
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
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
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE180100158
Funder
Australian Research Council
Funding Amount
$348,026.00
Summary
A large-scale distributed experimental facility for the internet of things. This project aims to establish a large-scale, real-world experimental facility for the Internet of Things (IoT), which is currently missing in Australia, as well as in the rest of the world. The project is expected to be an essential instrument to achieve Australia’s leadership on key enabling technologies of the IoT, and to provide Australian research community with a unique platform for large-scale experimentation and ....A large-scale distributed experimental facility for the internet of things. This project aims to establish a large-scale, real-world experimental facility for the Internet of Things (IoT), which is currently missing in Australia, as well as in the rest of the world. The project is expected to be an essential instrument to achieve Australia’s leadership on key enabling technologies of the IoT, and to provide Australian research community with a unique platform for large-scale experimentation and evaluation of IoT technologies and services. The project will also serve as a vehicle for the education and training of Australia’s next generation of scholars and engineers, and contribute to Australia’s scientific visibility.Read moreRead less
Managing private location data in a mobile and networked world: getting the balance right. Location based data are transforming the mobile service industry and this project will develop novel approaches to safeguard the location privacy of mobile individuals. This will facilitate the development of privacy-aware services which can be used for real time traffic monitoring, care for the elderly and smartphone enabled location services.
Algorithms for collaborative micro-navigation based on spatio-temporal data management and data mining. Traffic congestion coupled with greenhouse gas emissions is a major challenge for modern society. This project will tackle this challenge by developing computer-assisted smart vehicles that can access and exchange real-time information about traffic conditions, leading to improved driving experience, safety and environmental sustainability.
BigPrivacy: Scaling privacy preservation for big data applications on cloud. This project aims to research scalable privacy preservation for big data applications on cloud. Privacy preservation is a major concern for big data applications on cloud, such as health data analysis where user privacy must be preserved. Scalable solutions can preserve privacy so that data analysis such as health diagnosis can be performed quickly. The expected deliverable is a unified scalable privacy preservation fra ....BigPrivacy: Scaling privacy preservation for big data applications on cloud. This project aims to research scalable privacy preservation for big data applications on cloud. Privacy preservation is a major concern for big data applications on cloud, such as health data analysis where user privacy must be preserved. Scalable solutions can preserve privacy so that data analysis such as health diagnosis can be performed quickly. The expected deliverable is a unified scalable privacy preservation framework with associated algorithms and its prototype, which cloud systems can deploy for big data applications.Read moreRead less
Classifying Internet traffic for security applications. As the internet traffic data exponentially increases every year, traffic classification has become a fundamental approach to the security of the Internet. This project aims to develop a set of novel techniques for internet traffic classification, which is fundamentally important to defend against the serious cyber-attacks and effectively minimise the damages. This project is significant as it can help to improve cyber security, which is ess ....Classifying Internet traffic for security applications. As the internet traffic data exponentially increases every year, traffic classification has become a fundamental approach to the security of the Internet. This project aims to develop a set of novel techniques for internet traffic classification, which is fundamentally important to defend against the serious cyber-attacks and effectively minimise the damages. This project is significant as it can help to improve cyber security, which is essential for the work and daily lives of the Australian people. Furthermore, the proposed models and techniques will be important for enhancing the protection of Australian critical infrastructures against malicious cyber-attacks.Read moreRead less