Effective and Efficient Query Processing over Dynamic Social Networks. This project aims to invent novel query-based social network data exploration techniques which would help individuals or organisations make smart decisions based on data from increasingly massive, complex and dynamic social networks. Expected project outcomes are formal result semantics, advanced indices, efficient query evaluation algorithms and scalable techniques for three types of commonly used queries. The project plans ....Effective and Efficient Query Processing over Dynamic Social Networks. This project aims to invent novel query-based social network data exploration techniques which would help individuals or organisations make smart decisions based on data from increasingly massive, complex and dynamic social networks. Expected project outcomes are formal result semantics, advanced indices, efficient query evaluation algorithms and scalable techniques for three types of commonly used queries. The project plans to develop a system prototype to evaluate the effectiveness and efficiency of the proposed approaches and techniques. Query-based dynamic social network data exploration techniques developed in this project may have practical applications including event and influential topic discovery and tracking, buying trend analysis and political issues analysis.Read moreRead less
XML Views of Relational Databases: Semantics and Update Problems. XML is the standard for representing, publishing and exchanging data over the Internet and relational database is the dominant technology for data management. Updating XML views over relational data is fundamental to bring these two technologies together to serve Internet-based applications. Australia has been a leading country in both developing and applying internet technologies. The theoretic outcomes of this project will contr ....XML Views of Relational Databases: Semantics and Update Problems. XML is the standard for representing, publishing and exchanging data over the Internet and relational database is the dominant technology for data management. Updating XML views over relational data is fundamental to bring these two technologies together to serve Internet-based applications. Australia has been a leading country in both developing and applying internet technologies. The theoretic outcomes of this project will contribute to the advance in database and web research communities and establish us as an internationally leading group in this research area. The technological outcomes will help organisations in Australia effectively and efficiently conduct e-Business on the Internet. Read moreRead less
Comparative analysis and exploration of collections of data clusterings. Data clustering is an important technique for extracting knowledge from complex datasets. It is widely used by Australian science, government and industry, in areas such as genomics, proteomics, crime analysis, marketing and customer profiling. This project will develop new techniques that will allow users to explore and analyse collections of data clusterings. This will improve the current generation of clustering softw ....Comparative analysis and exploration of collections of data clusterings. Data clustering is an important technique for extracting knowledge from complex datasets. It is widely used by Australian science, government and industry, in areas such as genomics, proteomics, crime analysis, marketing and customer profiling. This project will develop new techniques that will allow users to explore and analyse collections of data clusterings. This will improve the current generation of clustering software and allow deeper investigation of challenging and complex data.
Read moreRead less
SeqSeeker: a search engine for large numbers of very long sequences. Large sets of very long sequences arise in many important domains. Well known examples are time series sequences in financial markets and meteorology and DNA and protein sequences in biology. This project will develop a search system, SeqSeeker, that can perform search on massive databases of such sequences. This will allow experts from many domains to get more value from their data and to investigate datasets which are cu ....SeqSeeker: a search engine for large numbers of very long sequences. Large sets of very long sequences arise in many important domains. Well known examples are time series sequences in financial markets and meteorology and DNA and protein sequences in biology. This project will develop a search system, SeqSeeker, that can perform search on massive databases of such sequences. This will allow experts from many domains to get more value from their data and to investigate datasets which are currently beyond the reach of today's technology.Read moreRead less
Advancing Analytical Query Processing with Urban Trajectory Data. This project aims to provide accurate, rapid, and comprehensive information to analyze transport and related infrastructure use in real time. This project expects to develop innovative solutions by exploiting massive urban trajectory data derived from public transport usage, route mapping, GPS tracking and road-side sensors. Expected outcomes include a new algorithmic framework to support complex trajectory-driven analytical tasks ....Advancing Analytical Query Processing with Urban Trajectory Data. This project aims to provide accurate, rapid, and comprehensive information to analyze transport and related infrastructure use in real time. This project expects to develop innovative solutions by exploiting massive urban trajectory data derived from public transport usage, route mapping, GPS tracking and road-side sensors. Expected outcomes include a new algorithmic framework to support complex trajectory-driven analytical tasks in public transport network planning, traffic congestion prevention, and facility deployment. This should significantly benefit both government and industry in data-driven decision makings and evaluations on the impact of decisions made, and ultimately materialize Australian government’s Smart Cities Plan.Read moreRead less
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
Effective and efficient keyword search for relevant entities over Extensible Markup Language (XML) data. This project aims to greatly improve the relevancy of returned XML entities by keyword queries as well as the efficiency of searching. Effective approaches and efficient algorithms for finding relevant entities from large number of XML data sources will be delivered.
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
Efficient and effective ad-hoc search using structured and unstructured geospatial information. Web search is a key enabling technology in the information age. However two technologies, ubiquitous mobile devices and massive structured data repositories such as those used to maintain social networking sites, are changing user expectations about how and what should be searched. A key challenge in the research community is how to integrate structured and unstructured information to improve the qual ....Efficient and effective ad-hoc search using structured and unstructured geospatial information. Web search is a key enabling technology in the information age. However two technologies, ubiquitous mobile devices and massive structured data repositories such as those used to maintain social networking sites, are changing user expectations about how and what should be searched. A key challenge in the research community is how to integrate structured and unstructured information to improve the quality of search. This project proposes new approaches to ranked retrieval for location-aware search. In particular, it presents a plan to combine state-of-the-art research from two domains: spatial keyword search in databases, and ad-hoc search in Information Retrieval to improve the quality of search results.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