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Research Topic : Affective computing
Field of Research : Database Management
Australian State/Territory : VIC
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  • Researchers (14)
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  • Active Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE190101118

    Funder
    Australian Research Council
    Funding Amount
    $339,000.00
    Summary
    High performance density-based clustering in parallel environments. This project aims to conduct a comprehensive study on density-based clustering to improve data management in parallel computing environments. Clustering, a fundamental task in data management, is to group a set of objects such that objects in the same group (called a cluster) are more similar to each other than those in other groups in order to simplify retrieval of similar information. Clustering is widely used in many fields i .... High performance density-based clustering in parallel environments. This project aims to conduct a comprehensive study on density-based clustering to improve data management in parallel computing environments. Clustering, a fundamental task in data management, is to group a set of objects such that objects in the same group (called a cluster) are more similar to each other than those in other groups in order to simplify retrieval of similar information. Clustering is widely used in many fields including machine learning, pattern recognition, information retrieval, bioinformatics and image analysis. It is expected that the developed clustering techniques will provide significant performance improvements in industry sectors where decisions are made based on clustering data analytics, such as the sectors of finance, renewable energy and artificial intelligence.
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    Funded Activity

    Discovery Projects - Grant ID: DP110100757

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    Managing private location data in a mobile and networked world: getting the balance right. Location based data are transforming the mobile service industry and this project will develop novel approaches to safeguard the location privacy of mobile individuals. This will facilitate the development of privacy-aware services which can be used for real time traffic monitoring, care for the elderly and smartphone enabled location services.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220101434

    Funder
    Australian Research Council
    Funding Amount
    $364,295.00
    Summary
    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.
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    Active Funded Activity

    ARC Future Fellowships - Grant ID: FT180100140

    Funder
    Australian Research Council
    Funding Amount
    $859,125.00
    Summary
    A ubiquitous system for indoor location-based services. This project aims to design a system capable of providing location-based services in WiFi-enabled indoor buildings. The project expects to address two major challenges hindering such a system, capability to identify a user's location in any indoor venue with minimum manual overhead, and effective data management techniques for indoor data. Expected outcomes of this project include new techniques for managing and utilising indoor location da .... A ubiquitous system for indoor location-based services. This project aims to design a system capable of providing location-based services in WiFi-enabled indoor buildings. The project expects to address two major challenges hindering such a system, capability to identify a user's location in any indoor venue with minimum manual overhead, and effective data management techniques for indoor data. Expected outcomes of this project include new techniques for managing and utilising indoor location data and enhanced international collaborations. The project will support and enhance a wide range of indoor applications such as emergency services, assisted healthcare systems, indoor asset tracking, event planning, indoor venue management, and consumer experience.
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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE130101002

    Funder
    Australian Research Council
    Funding Amount
    $375,000.00
    Summary
    Efficiently querying uncertain spatial space. Location-based services are becoming increasingly popular due to exponentially increased usage of smartphones and cheap wireless network. This project aims to provide efficient solutions for various location-based queries applicable to different travelling domains such as road networks, Euclidean space with obstacles and indoor space.
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    Funded Activity

    Discovery Projects - Grant ID: DP180103411

    Funder
    Australian Research Council
    Funding Amount
    $357,675.00
    Summary
    Next-generation search on social networks. This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in utilizing the geographical locations of queries and social network data to provide more relevant results, acknowledging and handling inherent uncertainties in the data, and exploiting knowledge graphs to produce intelligent search results. Expected outcomes of this project i .... Next-generation search on social networks. This project aims to design effective and intelligent search techniques for large scale social network data. The project expects to advance existing social network search systems in utilizing the geographical locations of queries and social network data to provide more relevant results, acknowledging and handling inherent uncertainties in the data, and exploiting knowledge graphs to produce intelligent search results. Expected outcomes of this project include a next-generation social network search system. The success of this project will support and enhance a wide range of applications such as law enforcement, health, national security, marketing, and advertisement.
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    Funded Activity

    Discovery Projects - Grant ID: DP150103710

    Funder
    Australian Research Council
    Funding Amount
    $216,000.00
    Summary
    Democratising Big Machine Learning. Technological advances such as cloud computing have disrupted thousands of businesses managing volatile compute loads. While elements of Big Data are now everywhere, still absent are wide-spread solutions for learning from data at scale-Big Machine Learning, the ultimate goal of Big Data. The greatest problems come not from a lack of distributed machine learning algorithms, but rather from preparing the data needed for fitting, evaluating and applying statisti .... Democratising Big Machine Learning. Technological advances such as cloud computing have disrupted thousands of businesses managing volatile compute loads. While elements of Big Data are now everywhere, still absent are wide-spread solutions for learning from data at scale-Big Machine Learning, the ultimate goal of Big Data. The greatest problems come not from a lack of distributed machine learning algorithms, but rather from preparing the data needed for fitting, evaluating and applying statistical models; often a manual, messy and costly process. This project proposes to develop advanced databases and statistical techniques for scalable and efficient data preparation, with the goal of bringing Big Machine Learning to a much broader range of users and businesses.
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    Funded Activity

    Discovery Projects - Grant ID: DP110102937

    Funder
    Australian Research Council
    Funding Amount
    $210,000.00
    Summary
    Efficient structure search over large graphs. The project aims to develop advanced search technology to support large-scale graph applications. The success of the project not only brings a breakthrough in technology development but also provides training for high quality personnel in this important and growing area, and brings considerable economic and social benefits to Australia.
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    Funded Activity

    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.
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    Showing 1-9 of 9 Funded Activites

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