Searching Cohesive Subgraphs in Big Attributed Graph Data. The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and ....Searching Cohesive Subgraphs in Big Attributed Graph Data. The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and efficient algorithms for searching and monitoring cohesive subgraphs in big and dynamic attributed graphs from both structure and attribute perspectives. The methods, techniques, and prototype systems developed in this project can be deployed to facilitate the smart use of big graph data across the nation. Read moreRead less
Modelling and Searching Cohesive Groups over Heterogeneous Graphs . Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for differen ....Modelling and Searching Cohesive Groups over Heterogeneous Graphs . Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for different applications and devise efficient algorithms for searching and monitoring those cohesive groups based on different models. The methods, techniques, and evaluation systems developed in this project can be deployed to facilitate the smart use of heterogeneous information networks across the nation.Read moreRead less
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
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
Next-generation Intelligent Explorations of Geo-located Data . This project aims to build a next-generation intelligent exploration framework over massive geo-located data, varying from points-of-interest to areas-of-interest data, in order to dramatically enhance user experiences when interacting with various forms of geo-located data over maps. Expected outcomes include novel exploration models, efficient and scalable algorithms for retrieving and visualizing the exploration results, online up ....Next-generation Intelligent Explorations of Geo-located Data . This project aims to build a next-generation intelligent exploration framework over massive geo-located data, varying from points-of-interest to areas-of-interest data, in order to dramatically enhance user experiences when interacting with various forms of geo-located data over maps. Expected outcomes include novel exploration models, efficient and scalable algorithms for retrieving and visualizing the exploration results, online updating of personal preferences during the life cycle of exploration, as well as a prototype system to evaluate and demonstrate practical value of the research. It will complement existing map services and significantly benefit many location-aware services, e.g., logistics, health services and urban planning.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
Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended ....Data-driven Traffic Analytics for Incident Analysis and Management. Traffic incidents are among the primary concerns of all transport authorities around the world due to their significant impact in terms of traffic congestion and delay, air and noise pollution, and management cost. This project aims to address incident analysis and management in complex and multi-modal traffic networks by combining multidisciplinary research efforts from transportation engineering and data science. The intended outcomes will be an innovative incident analysis and management framework synergising traffic data analytics and traffic simulation modelling as well as its key enabling techniques and prototype systems. This will significantly help mitigate incident impacts on daily commuters.Read moreRead less
A ubiquitous system for indoor location-based services. This project aims to design a system capable of providing location-based services in WiFi-enabled indoor buildings. The project expects to address two major challenges hindering such a system, capability to identify a user's location in any indoor venue with minimum manual overhead, and effective data management techniques for indoor data. Expected outcomes of this project include new techniques for managing and utilising indoor location da ....A ubiquitous system for indoor location-based services. This project aims to design a system capable of providing location-based services in WiFi-enabled indoor buildings. The project expects to address two major challenges hindering such a system, capability to identify a user's location in any indoor venue with minimum manual overhead, and effective data management techniques for indoor data. Expected outcomes of this project include new techniques for managing and utilising indoor location data and enhanced international collaborations. The project will support and enhance a wide range of indoor applications such as emergency services, assisted healthcare systems, indoor asset tracking, event planning, indoor venue management, and consumer experience.Read moreRead less