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Field of Research : Database Management
Socio-Economic Objective : Telecommunications
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  • Funded Activity

    Discovery Projects - Grant ID: DP0346004

    Funder
    Australian Research Council
    Funding Amount
    $169,000.00
    Summary
    Efficient Processing of Complex Spatial Queries. Similarity search and join are two of the most popular yet complex queiries in spatial databases. They are also two of the major spatial data analysis paradigms. To complement the existing techniques, this project aims to investigate a more complex and important form of these two problems, and to develop novel framework to approach the proposed problems. The successful achievements of the project will not only bring new spatial data analysis techn .... Efficient Processing of Complex Spatial Queries. Similarity search and join are two of the most popular yet complex queiries in spatial databases. They are also two of the major spatial data analysis paradigms. To complement the existing techniques, this project aims to investigate a more complex and important form of these two problems, and to develop novel framework to approach the proposed problems. The successful achievements of the project will not only bring new spatial data analysis techniques but also deliever effective solutions to a number of real-life apllications.
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    Funded Activity

    Discovery Projects - Grant ID: DP0663196

    Funder
    Australian Research Council
    Funding Amount
    $201,000.00
    Summary
    Data Mining by Clustering in Very Large Relational Databases. Many commercial and governmental entities possess very large relational data that cannot be feasibly analyzed by today's computers, e.g., gene expression data, product usage databases and telecommunication call records. The clustering tools developed in this project will have a significant benefit on many business processes that involve clustering this type of data, such as fraud detection and market segmentation.
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    Funded Activity

    Discovery Projects - Grant ID: DP0773483

    Funder
    Australian Research Council
    Funding Amount
    $168,000.00
    Summary
    PreferPeer: Towards Efficient Location-aware Preference Search in Mobile Peer-to-Peer Databases. 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 in very large scale highly mobile data. The proposed PreferPeer stands to open up major research directions in mobile point-to-point computing. Advances in this project will bring significant economic and social benefits to Austral .... PreferPeer: Towards Efficient Location-aware Preference Search in Mobile Peer-to-Peer Databases. 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 in very large scale highly mobile data. The proposed PreferPeer stands to open up major research directions in mobile point-to-point computing. Advances in this project will bring significant economic and social benefits to Australia. The research outcome of this project will directly benefit the following sectors: telecommunications, transportation, supply chain management, logistics, mobile computing, mobile e-commerce and marketing, air traffic control, defence, and so on, where efficient access to large amounts of highly mobile and distributed information is vital.
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    Funded Activity

    Discovery Projects - Grant ID: DP0880215

    Funder
    Australian Research Council
    Funding Amount
    $590,000.00
    Summary
    EPOS: Efficient Processing of Moving Object Streams in Data Management Systems. Advanced moving object data management systems are becoming a core technology for a large variety of applications such as traffic management and inventory tracking. These applications play a ubiquitous, critical role in our daily lives. In the same way as the first prototype of a relational database paved the way for successive relational database management systems, we envision that EPOS will form the foundation for .... EPOS: Efficient Processing of Moving Object Streams in Data Management Systems. Advanced moving object data management systems are becoming a core technology for a large variety of applications such as traffic management and inventory tracking. These applications play a ubiquitous, critical role in our daily lives. In the same way as the first prototype of a relational database paved the way for successive relational database management systems, we envision that EPOS will form the foundation for a new generation of moving object databases. EPOS is designed to process a large number of concurrently running continuous monitoring queries on a massive set of moving objects with frequent updates.
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    Showing 1-4 of 4 Funded Activites

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