Efficient Similarity Query Processing in High Dimensional Databases. This project studies a fundamental problem common to a wide range of applications. It contributes to smart use of information, which is vital to the modern knowledge-based economy, by providing an enabling technology to capitalise Australia's huge investment in data collection. Our research is right in the forefront of ICT research, leading the international effort of extending database technologies to support data management a ....Efficient Similarity Query Processing in High Dimensional Databases. This project studies a fundamental problem common to a wide range of applications. It contributes to smart use of information, which is vital to the modern knowledge-based economy, by providing an enabling technology to capitalise Australia's huge investment in data collection. Our research is right in the forefront of ICT research, leading the international effort of extending database technologies to support data management and query processing for very large and highly complex data.Read moreRead less
QualA-D: a quality aware query engine for next generation data integration systems. This project will address the growing diversity of the web/user community by developing new approaches for data integration that incorporate data quality requirements such as data currency, completeness and coverage. First-of-breed quality aware query system is expected to be developed that will assist in improving user experience and satisfaction.
Effective Recommendations based on Multi-Source Data. Large-scale data collected from multiple sources such as the Web, sensor networks, academic publications, and social networks provide a new opportunity to exploit useful information for effective and efficient recommendations and decision making. The project will propose a new framework of recommender systems that is based on analysing relationships between different types of objects from multiple data sources. A graph model will be built to ....Effective Recommendations based on Multi-Source Data. Large-scale data collected from multiple sources such as the Web, sensor networks, academic publications, and social networks provide a new opportunity to exploit useful information for effective and efficient recommendations and decision making. The project will propose a new framework of recommender systems that is based on analysing relationships between different types of objects from multiple data sources. A graph model will be built to represent the extracted semantic relationships and novel linkage-analysis based algorithms will be developed for ranking objects. The results from this project will underpin many critical applications such as healthcare.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
Discovery Early Career Researcher Award - Grant ID: DE140100215
Funder
Australian Research Council
Funding Amount
$394,752.00
Summary
Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genui ....Searching Activity Trajectories for Intention Oriented Recommendations. The ubiquitous fusion of social network services and Global Positioning System-enabled mobile devices has generated large-scale activity trajectory data representing the footprint of people's daily activities. It presents an unprecedented opportunity to build highly intelligent recommendation systems. Existing approaches that merely focus on the location aspect of trajectories are limited in their ability to understand genuine preferences from travel histories, due to lack of consideration for activity information as well as the associated semantics and context. This project aims to address these issues and provide effective recommendations by considering both users’ intention and collective behavioural knowledge inferred from activity trajectories.Read moreRead less
Monitoring social events for user online behaviour analytics. This project aims to investigate the influence of public attention on steering user online behaviour. The exponential growth of online behaviour data makes online behaviour analytics increasingly important in social, commercial and political environments, but existing methods rely on user profiles only. The project will unify external social events with user profiles for behaviour analytics, and develop approaches for event database i ....Monitoring social events for user online behaviour analytics. This project aims to investigate the influence of public attention on steering user online behaviour. The exponential growth of online behaviour data makes online behaviour analytics increasingly important in social, commercial and political environments, but existing methods rely on user profiles only. The project will unify external social events with user profiles for behaviour analytics, and develop approaches for event database indexing, event-influenced behaviour modelling and prediction. The success of this project is expected to enhance users’ online experience and improve e-commerce’s market value.Read moreRead less
Managing data with high redundancy and low value density. This project aims to develop a database for data storage, cleaning, compression, hierarchal summarisation, indexing and query processing for machination data.Database management systems are needed to support stream query processing and manage historical data to support complex data analytics, data mining and data-driven decision making. Machination data, often found in sensor networks, GPS and RFID applications, vehicle on-board devices a ....Managing data with high redundancy and low value density. This project aims to develop a database for data storage, cleaning, compression, hierarchal summarisation, indexing and query processing for machination data.Database management systems are needed to support stream query processing and manage historical data to support complex data analytics, data mining and data-driven decision making. Machination data, often found in sensor networks, GPS and RFID applications, vehicle on-board devices and medical monitoring devices are difficult to manage and process because of large volumes and streaming, high redundancy and low value density. This project is expected to stream machination data management to support scalable query processing and data analytics.Read moreRead less
Special Research Initiatives - Grant ID: SR0567393
Funder
Australian Research Council
Funding Amount
$100,000.00
Summary
Infrastructure for large-scale data resource sharing between research institutions – an environmental case study. The project creates a federated distributed data infrastructure for research, that encourages data creators to make their data available to other scientists, and encourages users to make use of data available from many sources. The vision is to establish an ICT infrastructure to facilitate a whole-of-environment approach to environmental research. The outcome is a proof-of-concept ....Infrastructure for large-scale data resource sharing between research institutions – an environmental case study. The project creates a federated distributed data infrastructure for research, that encourages data creators to make their data available to other scientists, and encourages users to make use of data available from many sources. The vision is to establish an ICT infrastructure to facilitate a whole-of-environment approach to environmental research. The outcome is a proof-of-concept application based upon a case study of Queensland Environmental Protection Agency’s databases, to gain an in-depth understanding of the complexity, scope and key technological barriers for establishing an ICT infrastructure, to identify where the latest technologies can be used and where the gaps are for these technologies to be used in environmental sciences.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
Integrating Database Technologies and Visual Analysis in Bioinformatics for Genome Data. Solving modern biological problems, especially those involving genome data, requires advanced computational and analytical methods. The huge quantities of data and escalating demands of modern biological research increasingly require the sophistication and power of object-relational database tools. Key techniques include relational data management, pattern recognition, data mining and visualization of biolog ....Integrating Database Technologies and Visual Analysis in Bioinformatics for Genome Data. Solving modern biological problems, especially those involving genome data, requires advanced computational and analytical methods. The huge quantities of data and escalating demands of modern biological research increasingly require the sophistication and power of object-relational database tools. Key techniques include relational data management, pattern recognition, data mining and visualization of biological data. In this project we will develop efficient methodologies and data structures for gathering high-quality approximations of full genomic information, and will use these innovations as the foundation to develop novel, practical tools for clustering and visualization in genomic data mining and database management.
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