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Field of Research : Database Management
Field of Research : Data Format
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  • Active Funded Activity

    Discovery Projects - Grant ID: DP200103700

    Funder
    Australian Research Council
    Funding Amount
    $450,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0559005

    Funder
    Australian Research Council
    Funding Amount
    $193,000.00
    Summary
    New Directions in Mining Complex Spatial Relationships in Large Scientific Databases. International and Australian organizations are investing in large projects involving the collection of terabytes of scientific data. The Anglo-Australian Galaxy Redshift Survey in eastern Australia has obtained data for a quarter of a million galaxies. Similarly the Tropical Ocean Global Atmophere(TOGA) program is being expanded to collect data from the equatorial pacific region which will help better understa .... New Directions in Mining Complex Spatial Relationships in Large Scientific Databases. International and Australian organizations are investing in large projects involving the collection of terabytes of scientific data. The Anglo-Australian Galaxy Redshift Survey in eastern Australia has obtained data for a quarter of a million galaxies. Similarly the Tropical Ocean Global Atmophere(TOGA) program is being expanded to collect data from the equatorial pacific region which will help better understand the El Nino/Southern Oscillation Cycle. We are developing powerful spatial data mining tools which will go a long way in finding potential nuggets of useful information in these large databases and help Australian and international scientists hypothesise new theories to explain the underlying phenomenon.
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    Funded Activity

    Discovery Projects - Grant ID: DP0770479

    Funder
    Australian Research Council
    Funding Amount
    $165,708.00
    Summary
    Privacy Protection in Distributed Data Mining. Information and Communications Technology (ICT) has dramatically altered the world's social and economic landscape. 'From data to knowledge' is one of the priority challenges recognized by National ICT Australia. However, privacy concerns may prevent it from realization. This project aims to fulfil 'from data to knowledge' without breaching privacy of data from distributed resources held by different parties. The outcomes of this project will create .... Privacy Protection in Distributed Data Mining. Information and Communications Technology (ICT) has dramatically altered the world's social and economic landscape. 'From data to knowledge' is one of the priority challenges recognized by National ICT Australia. However, privacy concerns may prevent it from realization. This project aims to fulfil 'from data to knowledge' without breaching privacy of data from distributed resources held by different parties. The outcomes of this project will create new directions in the research of privacy-preserving distributed data mining and are applicable to Australian counter-terrorism and homeland defence in detecting bio-terrorism from privacy sensitive data.
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    Funded Activity

    Discovery Projects - Grant ID: DP0878405

    Funder
    Australian Research Council
    Funding Amount
    $255,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP110102407

    Funder
    Australian Research Council
    Funding Amount
    $335,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0988411

    Funder
    Australian Research Council
    Funding Amount
    $190,000.00
    Summary
    Private Data Warehouse Query. Information and Communications Technology (ICT) has dramatically altered the world's social and economic landscape. 'From data to knowledge' is one of priority challenges recognized by National ICT Australia. However, privacy concern may prevent it from realisation. This project aims to fulfil 'from data to knowledge' without breaching privacy of user's queries to a data warehouse. The outcomes of this project will create new directions in the research of private da .... Private Data Warehouse Query. Information and Communications Technology (ICT) has dramatically altered the world's social and economic landscape. 'From data to knowledge' is one of priority challenges recognized by National ICT Australia. However, privacy concern may prevent it from realisation. This project aims to fulfil 'from data to knowledge' without breaching privacy of user's queries to a data warehouse. The outcomes of this project will create new directions in the research of private data warehouse query, and are applicable to stock exchange data warehouses and pharmaceutical data warehouses, where the user is reluctant to reveal his query to the data warehouse operator.
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    Funded Activity

    Discovery Projects - Grant ID: DP140103499

    Funder
    Australian Research Council
    Funding Amount
    $373,250.00
    Summary
    On Effectively Answering Why and Why-not Questions in Databases. While the performance and functionality of database systems have gained dramatic improvement, research on improving usability still remains far behind, which results in huge cost of technical support to organisations. This project aims to improve the usability of database systems by effectively answering users' why and why-not questions on query results. This project will invent a novel and generalised model for expressing both the .... On Effectively Answering Why and Why-not Questions in Databases. While the performance and functionality of database systems have gained dramatic improvement, research on improving usability still remains far behind, which results in huge cost of technical support to organisations. This project aims to improve the usability of database systems by effectively answering users' why and why-not questions on query results. This project will invent a novel and generalised model for expressing both the why and why-not questions, efficient strategies for answering questions for complex queries and databases, and novel solutions to scenarios that involve multiple queries. The project will contribute greatly to the fundamental research in query refinement and deliver significant impact on related technology development.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220102191

    Funder
    Australian Research Council
    Funding Amount
    $415,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP170104747

    Funder
    Australian Research Council
    Funding Amount
    $341,000.00
    Summary
    Biclique discovery in Big Data. This project aims to design algorithms to capture Big Data. Biclique is a popular graph model that can capture important cohesive structures in many applications. However, traditional biclique discovery algorithms which only focus on simple, small-scale, static and deterministic data are inadequate in the era of Big Data where data has Variety (various formats), Volume (large quantity), Velocity (dynamic update) and Veracity (uncertainty). This project expects to .... Biclique discovery in Big Data. This project aims to design algorithms to capture Big Data. Biclique is a popular graph model that can capture important cohesive structures in many applications. However, traditional biclique discovery algorithms which only focus on simple, small-scale, static and deterministic data are inadequate in the era of Big Data where data has Variety (various formats), Volume (large quantity), Velocity (dynamic update) and Veracity (uncertainty). This project expects to benefit real applications in both public and private sectors and add value to Australian manufactured products.
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