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
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
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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Protect information sharing within distributed collaborative environment. Industries require secure information accessing and communication. This project continues development of new delegation frameworks and information assurance requirements in Internet-based collaborative environments. The frameworks will be systematically upon policy-based models to set up a reliable, secure information sharing and communication medium. We also aim to develop techniques for setting up secure group communic ....Protect information sharing within distributed collaborative environment. Industries require secure information accessing and communication. This project continues development of new delegation frameworks and information assurance requirements in Internet-based collaborative environments. The frameworks will be systematically upon policy-based models to set up a reliable, secure information sharing and communication medium. We also aim to develop techniques for setting up secure group communication and providing accesses to group members for many database systems. The approach leads to a great understanding of advocating selective information sharing in role-based systems. The project develops fundamental enabling methodologies for the information and communication industry.Read moreRead less
Limiting disclosure of private information in relational database systems. Enterprises are deeply concerned about customers' privacy issues and try to build solid trust to attract customers. This project continues development of new purpose-based frameworks and private information assurance requirements in relational database systems. The frameworks will identify and address issues of protecting private information; and to specify and enforce privacy rules to support identified issues. It aim ....Limiting disclosure of private information in relational database systems. Enterprises are deeply concerned about customers' privacy issues and try to build solid trust to attract customers. This project continues development of new purpose-based frameworks and private information assurance requirements in relational database systems. The frameworks will identify and address issues of protecting private information; and to specify and enforce privacy rules to support identified issues. It aims to develop techniques for purpose-based usage control and detecting possible conflicts between obligations. The approach leads to a great understanding of advocating limited disclosure in usage control systems. The project develops fundamental enabling methodologies for the information and communication industry.Read moreRead less
Making Spatiotemporal Data More Useful: An Entity Linking Approach. This project aims to establish a methodology for spatiotemporal entity linking by utilising object movement traces to support database integration and data quality management for the next-generation of data where spatiotemporal attributes are ubiquitous. It expects to develop a novel entity linking paradigm for automatic, efficient and reliable spatiotemporal data integration together with a new data privacy study in this contex ....Making Spatiotemporal Data More Useful: An Entity Linking Approach. This project aims to establish a methodology for spatiotemporal entity linking by utilising object movement traces to support database integration and data quality management for the next-generation of data where spatiotemporal attributes are ubiquitous. It expects to develop a novel entity linking paradigm for automatic, efficient and reliable spatiotemporal data integration together with a new data privacy study in this context. Expected outcome include new database technologies for data signature generation and similarity-based search, and improved location data privacy protection methods. This project should provide significant benefits to all areas where high quality spatiotemporal data fusion is essential to meaningful data analysis.Read moreRead less
Learning human activities through low cost, unobtrusive RFID technology. A rapidly growing aged population presents many challenges to Australia's health and aged care services. The outcomes of this project will help aging Australians live in their own homes longer, with greater independence and safety by providing an automated, unobtrusive means for health professionals to monitor activity and intervene as required.