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Research Topic : tissue storage
Australian State/Territory : VIC
Field of Research : Data Structures
Status : Closed
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  • Funded Activity

    Discovery Projects - Grant ID: DP0558916

    Funder
    Australian Research Council
    Funding Amount
    $324,923.00
    Summary
    Using Past Queries for Fast and Accurate Web Searching. Searching the entire Internet, or a company web site, has become a vital task for modern organisations. While there has been significant research into improving search engines through using web pages themselves, very little attention has been paid to improving web search by exploiting the vast numbers of queries that users submit to search engines each day. This project will use state of the art compression and algorithmic techniques to imp .... Using Past Queries for Fast and Accurate Web Searching. Searching the entire Internet, or a company web site, has become a vital task for modern organisations. While there has been significant research into improving search engines through using web pages themselves, very little attention has been paid to improving web search by exploiting the vast numbers of queries that users submit to search engines each day. This project will use state of the art compression and algorithmic techniques to improve the speed and accuracy of web search using data gleaned from millions of Internet queries (provided under agreement by Microsoft). Improving search engines will have a direct benefit to many Australian industries, and support the government's priority area of "smart information use".
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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: 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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    Funded Activity

    Discovery Early Career Researcher Award - Grant ID: DE140100275

    Funder
    Australian Research Council
    Funding Amount
    $392,979.00
    Summary
    Beyond keyword search for ranked document retrieval. This project will develop novel approaches to efficient and effective ranked text retrieval using a new class of rank-aware algorithms derived from self-indexes. These algorithms can support complex statistical calculations on the fly. Efficient algorithm design for big data is an increasingly important problem as energy costs continue to soar and can now exceed hardware costs for big data consumers such as Google. In this project, two importa .... Beyond keyword search for ranked document retrieval. This project will develop novel approaches to efficient and effective ranked text retrieval using a new class of rank-aware algorithms derived from self-indexes. These algorithms can support complex statistical calculations on the fly. Efficient algorithm design for big data is an increasingly important problem as energy costs continue to soar and can now exceed hardware costs for big data consumers such as Google. In this project, two important problems in web search are explored: real-time indexing and long-form query answering. Using self-index algorithms, this project presents a road map to move beyond simple keyword-based ranked document retrieval, thus allowing us to efficiently meet more demanding information needs of users in the next decade.
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    Funded Activity

    Discovery Projects - Grant ID: DP160102412

    Funder
    Australian Research Council
    Funding Amount
    $311,000.00
    Summary
    Identifying and Tracking Influential Events in Large Social Networks. This project aims to invent a novel model and techniques for identifying and tracking influential events in large and dynamic social networks in real time. The proposed model would take into account the structure and content of social networks, and the influence of events. The project also plans to develop efficient strategies for identifying and tracking events in large and dynamic social network environments based on the mod .... Identifying and Tracking Influential Events in Large Social Networks. This project aims to invent a novel model and techniques for identifying and tracking influential events in large and dynamic social networks in real time. The proposed model would take into account the structure and content of social networks, and the influence of events. The project also plans to develop efficient strategies for identifying and tracking events in large and dynamic social network environments based on the model, In particular, the project plans to investigate flexible social network query methods to make users’ event search easy. Finally the project plans to build an evaluation system to demonstrate the efficiency of the algorithms and effectiveness of the model.
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    Funded Activity

    Discovery Projects - Grant ID: DP110101743

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Efficient and effective algorithms for searching strings in secondary storage. Pattern searching is fundamental to a wide range of computing applications, including web search and bioinformatics. In this project we will develop compression algorithms and hybrid memory-disk search structures that allow fast pattern matching on sequences of textual and numeric data, including when approximate search is required.
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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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    Funded Activity

    Discovery Projects - Grant ID: DP120102627

    Funder
    Australian Research Council
    Funding Amount
    $320,000.00
    Summary
    On effectively modelling and efficiently discovering communities from large networks. Finding and maintaining close communities from very large scale, dynamically changing networks is interesting and challenging. This project aims to develop new techniques to identify such communities as fast as possible through exploiting the rich semantics and individual relationships within the communities.
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    Funded Activity

    Discovery Projects - Grant ID: DP0771504

    Funder
    Australian Research Council
    Funding Amount
    $246,090.00
    Summary
    Efficient Algorithms for In-memory Sorting, Searching and Indexing on Modern Multi-core Cache-based and Graphics Processor Architectures. This project clearly belongs to one of the national research priority goals, Smart Information Use. The copy-based techniques and work on sorting and searching will considerably impact the development of in-memory algorithms in cutting-edge computer architectures. Efficient suffix trees and suffix sorting have myriad applications in string-processing and will .... Efficient Algorithms for In-memory Sorting, Searching and Indexing on Modern Multi-core Cache-based and Graphics Processor Architectures. This project clearly belongs to one of the national research priority goals, Smart Information Use. The copy-based techniques and work on sorting and searching will considerably impact the development of in-memory algorithms in cutting-edge computer architectures. Efficient suffix trees and suffix sorting have myriad applications in string-processing and will be of high interest to bioinformatics companies. The sortdex project will develop novel algorithms that will be used by enterprise search engine companies to develop applications for libraries and organisations dealing with large databases. Algorithms using the graphics processor as a co-processor have important applications in the high-growth field of computer graphics and games.
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    Funded Activity

    Discovery Projects - Grant ID: DP0666154

    Funder
    Australian Research Council
    Funding Amount
    $227,000.00
    Summary
    Development and Application of Techniques for Detecting Equivalent Documents. The web is a vast collection of data, such as text and images, but contains large numbers of duplicates - the same document or picture may be present many times. Even personal collections of information, such as the documents and digital photos people keep on their home computers, often have many versions of the same item. However, detecting such duplicates is not straightforward, as they may have been edited, or may, .... Development and Application of Techniques for Detecting Equivalent Documents. The web is a vast collection of data, such as text and images, but contains large numbers of duplicates - the same document or picture may be present many times. Even personal collections of information, such as the documents and digital photos people keep on their home computers, often have many versions of the same item. However, detecting such duplicates is not straightforward, as they may have been edited, or may, for example, be shown in different forms; for example, the quality of a photo may be reduced for display on a mobile phone. In this project we plan to detect such duplicates, and use the results to improve search and management of data.
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