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.Read moreRead less
Mining multi-typed and dynamic graphs. Large volumes of data collected nowadays from real-world applications are often represented as graphs. The nodes and the edges of such graphs represent different types of entities and interactions, and they have time information. This project will develop algorithms that mine efficiently such multi-typed and dynamic graphs.
Analyzing Uncertain Data: Probabilistic Approaches. The expected research outcome includes siginificantly technical contributions to the uncertain data analysis technology development by supporting probablistic query procesing. The proposed systematic, algorithm and database centric approach to investigate the novel, ubiquitous problems will lead to a greater support, from the database community, to the advanced real applications, and creating new opportunities for the IT industry. The success o ....Analyzing Uncertain Data: Probabilistic Approaches. The expected research outcome includes siginificantly technical contributions to the uncertain data analysis technology development by supporting probablistic query procesing. The proposed systematic, algorithm and database centric approach to investigate the novel, ubiquitous problems will lead to a greater support, from the database community, to the advanced real applications, and creating new opportunities for the IT industry. The success of this project will not only further enhance us as an internationally leading research group in uncertain data analysis and provide training for high quality personnel in this important and growing area but also bring considerable economic and social benefits to Australia.Read moreRead less
Computing Order Statistcs over Data Streams. While data stream computation currently is one of the most challenging areas in IT research community, order statistics computation is a very important topic in data stream computation.
This project aims to deliver advanced techniques that promise a great impact on data stream technology. The success of this project will give another competitive edge for Australia to continue her leading role in the development of core IT technology. Moreover,
the ....Computing Order Statistcs over Data Streams. While data stream computation currently is one of the most challenging areas in IT research community, order statistics computation is a very important topic in data stream computation.
This project aims to deliver advanced techniques that promise a great impact on data stream technology. The success of this project will give another competitive edge for Australia to continue her leading role in the development of core IT technology. Moreover,
the research outcome of the project will provide generic solutions to many Australia based
industries, including e-finance, telecommunication, network management, sensor network technology
development, and environment monitoring.
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Effectively Computing and Maintaining Graph-based Statistics in Large Scale Applications. The expected research outcome includes significantly technical contributions to the graph-based query processing technology development by supporting on-line data analysis. The proposed systematic, algorithm and database centric approach to investigate the novel, ubiquitous problems will lead to a greater support, from the database community, to the advanced real applications, and to creating new opportunit ....Effectively Computing and Maintaining Graph-based Statistics in Large Scale Applications. The expected research outcome includes significantly technical contributions to the graph-based query processing technology development by supporting on-line data analysis. The proposed systematic, algorithm and database centric approach to investigate the novel, ubiquitous problems will lead to a greater support, from the database community, to the advanced real applications, and to creating new opportunities for the IT industry. The success of this project will not only further enhance us as an internationally leading research group in data statistics computation and provide training for high quality personnel in this important and growing area but also bring considerable economic and social benefits to Australia.Read moreRead less
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.