Discovery Early Career Researcher Award - Grant ID: DE210101808
Funder
Australian Research Council
Funding Amount
$395,775.00
Summary
Genetic Programming for Big Data Analytics. The project aims to extend a powerful machine learning method, called genetic programming and also developing a new concept called Alpha program, for big data analytics. This project expects to generate a new approach by finding a systematic approach to develop gene structures using information theory. By borrowing the best genes from the population of programs, the Alpha program concept will be developed for the first time. The proposed approach aims ....Genetic Programming for Big Data Analytics. The project aims to extend a powerful machine learning method, called genetic programming and also developing a new concept called Alpha program, for big data analytics. This project expects to generate a new approach by finding a systematic approach to develop gene structures using information theory. By borrowing the best genes from the population of programs, the Alpha program concept will be developed for the first time. The proposed approach aims to enhance genetic programming for many practical problems. I contend that not only finding better tools for big data analytics is in the best interest of machine learning and big data communities, it also provides significant benefits for other communities and industries in Australia.Read moreRead less
Integrating deep-earth and surface processes for frontier-basin exploration. It is well-known that mantle convection has a profound influence on basin evolution, and the next step will be to quantify this relationship and provide the science that will make these concepts applicable to exploration. To do this, we will develop a workflow to link plate-reconstruction software with the mantle convection modelling to link plate motions mantle convection and the history of sedimentation systematically ....Integrating deep-earth and surface processes for frontier-basin exploration. It is well-known that mantle convection has a profound influence on basin evolution, and the next step will be to quantify this relationship and provide the science that will make these concepts applicable to exploration. To do this, we will develop a workflow to link plate-reconstruction software with the mantle convection modelling to link plate motions mantle convection and the history of sedimentation systematically for the first time for frontier basin-scale applications. We will apply these emerging technologies to the evolution of basins in the Arctic borderlands frontier for resource exploration and on the Australian continent.Read moreRead less
Dynamic Load Balancing for Systems under Heavy Traffic Demand and High Task Size Variation. Current computer systems cannot cope with extremely heavy traffic demands. A solution to such a difficult problem is to dynamically balance the load across the system's servers. Several solutions have been proposed and demonstrate advances in certain limited conditions (e.g. uniform distribution). However fundamental research work must be undertaken beyond the current way of dealing with the core issues o ....Dynamic Load Balancing for Systems under Heavy Traffic Demand and High Task Size Variation. Current computer systems cannot cope with extremely heavy traffic demands. A solution to such a difficult problem is to dynamically balance the load across the system's servers. Several solutions have been proposed and demonstrate advances in certain limited conditions (e.g. uniform distribution). However fundamental research work must be undertaken beyond the current way of dealing with the core issues of load balancing. Accounting for realistic conditions is a theoretical and practical challenge. This project aims at developing theoretical and computational models for dynamic task distribution for the studied systems. The benefits include substantial improvement of the system response time.Read moreRead less
Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require c ....Approximate structures for efficient processing of data streams. This project aims to increase the volume of streamed data that can be handled on a low-powered device with limited memory. In finance, health, and transport, data arrives at enormous rates, and data-driven decisions must be made quickly. Likewise, to keep Australia secure, national agencies monitor and gather vast data sets. Increasingly, devices and monitors that have limited resources are making these decisions and they require computational techniques that run extremely efficiently. The project expects to develop and improve approximate data structures that operate in tight resource bounds. Anticipated outcomes are improved event recognition and dramatic speedup in analysis of streams in areas such as finance, health, transport, and urban data.Read moreRead less
Data Structures for Multi-Core. The project intends to improve data structures to reduce the bottleneck effect caused by multiple processor cores. The hardware used for a typical server platform has increasing numbers of processor cores. This growing number of cores creates a bottleneck effect when accessing the data that are structured in the shared memory of these servers. These contended data structures limit the server performance and new algorithms are necessary. The project proposes to rel ....Data Structures for Multi-Core. The project intends to improve data structures to reduce the bottleneck effect caused by multiple processor cores. The hardware used for a typical server platform has increasing numbers of processor cores. This growing number of cores creates a bottleneck effect when accessing the data that are structured in the shared memory of these servers. These contended data structures limit the server performance and new algorithms are necessary. The project proposes to relax traditional consistency criteria to provide high concurrency and to leverage optimistic executions that proceed concurrently but may roll back depending on the conflicts with other concurrent executions they encounter. The concurrent data structures would allow application performance to scale with higher numbers of hardware cores.Read moreRead less
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. Read moreRead less
Making Spatiotemporal Data More Useful: An Entity Linking Approach. This project aims to establish a methodology for spatiotemporal entity linking by utilising object movement traces to support database integration and data quality management for the next-generation of data where spatiotemporal attributes are ubiquitous. It expects to develop a novel entity linking paradigm for automatic, efficient and reliable spatiotemporal data integration together with a new data privacy study in this contex ....Making Spatiotemporal Data More Useful: An Entity Linking Approach. This project aims to establish a methodology for spatiotemporal entity linking by utilising object movement traces to support database integration and data quality management for the next-generation of data where spatiotemporal attributes are ubiquitous. It expects to develop a novel entity linking paradigm for automatic, efficient and reliable spatiotemporal data integration together with a new data privacy study in this context. Expected outcome include new database technologies for data signature generation and similarity-based search, and improved location data privacy protection methods. This project should provide significant benefits to all areas where high quality spatiotemporal data fusion is essential to meaningful data analysis.Read moreRead less
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.Read moreRead less
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.Read moreRead less
New approaches to interactive sessional search for complex tasks. This project aims to develop new tools and techniques to improve the accuracy and speed of search and data analytics for complex information tasks. There are currently no publicly available search engines which support users engaged in complex interactive search, or that allow searchers to fully control their own data and privacy. Fundamental research advances, based on understanding real user behaviour and search needs will have ....New approaches to interactive sessional search for complex tasks. This project aims to develop new tools and techniques to improve the accuracy and speed of search and data analytics for complex information tasks. There are currently no publicly available search engines which support users engaged in complex interactive search, or that allow searchers to fully control their own data and privacy. Fundamental research advances, based on understanding real user behaviour and search needs will have an impact on important academic, industrial, and government domains, including virtual assistants, health care (clinical decision support), precision medicine, eDiscovery, crime prevention, and detailed socio-economic evaluations.Read moreRead less