Scaling Disk-Resident Learned Indexes For Database Systems. This project aims to investigate new disk-resident learned indexing algorithms to store and process data in database systems by advancing the state-of-the-art in memory-resident learned modeling. This project expects to generate new knowledge in the area of digital storage technologies utilising novel and efficient techniques in learned indexing for big data. This should provide significant benefits to enable modern database systems to ....Scaling Disk-Resident Learned Indexes For Database Systems. This project aims to investigate new disk-resident learned indexing algorithms to store and process data in database systems by advancing the state-of-the-art in memory-resident learned modeling. This project expects to generate new knowledge in the area of digital storage technologies utilising novel and efficient techniques in learned indexing for big data. This should provide significant benefits to enable modern database systems to scale with the massive growth of data, improve the efficiency of data processing, improve the effectiveness of projects that utilise big data, and dramatically reduce energy costs in Australian data centres when storing and retrieving data from databases and lower their carbon footprints.Read moreRead less
Effective and Efficient Query Processing over Dynamic Social Networks. This project aims to invent novel query-based social network data exploration techniques which would help individuals or organisations make smart decisions based on data from increasingly massive, complex and dynamic social networks. Expected project outcomes are formal result semantics, advanced indices, efficient query evaluation algorithms and scalable techniques for three types of commonly used queries. The project plans ....Effective and Efficient Query Processing over Dynamic Social Networks. This project aims to invent novel query-based social network data exploration techniques which would help individuals or organisations make smart decisions based on data from increasingly massive, complex and dynamic social networks. Expected project outcomes are formal result semantics, advanced indices, efficient query evaluation algorithms and scalable techniques for three types of commonly used queries. The project plans to develop a system prototype to evaluate the effectiveness and efficiency of the proposed approaches and techniques. Query-based dynamic social network data exploration techniques developed in this project may have practical applications including event and influential topic discovery and tracking, buying trend analysis and political issues analysis.Read moreRead less
Big temporal graph processing in the Cloud. This project aims to develop efficient and scalable algorithms to process big temporal graphs in the Cloud. In particular, we will investigate three most representative types of queries over big temporal graphs including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big temporal graphs as well as a system prototype for evaluation ....Big temporal graph processing in the Cloud. This project aims to develop efficient and scalable algorithms to process big temporal graphs in the Cloud. In particular, we will investigate three most representative types of queries over big temporal graphs including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big temporal graphs as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications such as cybersecurity, e-commerce, health and road networks.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE240100668
Funder
Australian Research Council
Funding Amount
$435,000.00
Summary
Towards Processing of Big Streaming Temporal Graphs. This project aims to develop efficient and scalable algorithms to process big streaming temporal graphs, which is in high demand for many data-intensive applications such as cybersecurity, crime monitoring, and e-marketing. In particular, I will investigate three most representative types of queries including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations ....Towards Processing of Big Streaming Temporal Graphs. This project aims to develop efficient and scalable algorithms to process big streaming temporal graphs, which is in high demand for many data-intensive applications such as cybersecurity, crime monitoring, and e-marketing. In particular, I will investigate three most representative types of queries including vertex-based queries, path-based queries, and subgraph-based queries. Expected outcomes of this project include theoretical foundations and scalable algorithms to process big streaming temporal graphs as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications such as cybersecurity, e-commerce, health and social analysis.Read moreRead less
Next-Generation Distributed Graph Engine for Big Graphs. This project aims to develop an efficient and scalable distributed graph engine to process big graphs. In particular, we will investigate the foundations for the distributed real-time graph engine, focusing on graph storage and graph operators, and then provide solutions for a set of representative graph mining and query processing tasks. Expected outcomes of this project include theoretical foundations and a scalable real-time graph engin ....Next-Generation Distributed Graph Engine for Big Graphs. This project aims to develop an efficient and scalable distributed graph engine to process big graphs. In particular, we will investigate the foundations for the distributed real-time graph engine, focusing on graph storage and graph operators, and then provide solutions for a set of representative graph mining and query processing tasks. Expected outcomes of this project include theoretical foundations and a scalable real-time graph engine to process big graphs as well as a system prototype for evaluation and to demonstrate the practical value. Success in this project should see significant benefits for many important applications such as cybersecurity, e-commerce, health and road networks.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170100641
Funder
Australian Research Council
Funding Amount
$305,754.00
Summary
Priced attribute-based encryption and its applications. This project aims to develop Priced Attribute-Based Encryption (PABE), a security mechanism. Access control is important for secure online information access. Access to encrypted data requires both private key and payment from earmarked funds specified by the access policy of encrypted data. This research will enable both authorisation and restriction of users while they access protected data anonymously. Expected outcomes include new model ....Priced attribute-based encryption and its applications. This project aims to develop Priced Attribute-Based Encryption (PABE), a security mechanism. Access control is important for secure online information access. Access to encrypted data requires both private key and payment from earmarked funds specified by the access policy of encrypted data. This research will enable both authorisation and restriction of users while they access protected data anonymously. Expected outcomes include new models, theories, techniques and PABE constructions. This research project is expected to contribute to cyber security in anonymous access control with advanced management for all Australians.Read moreRead less
Monitoring online topic evolvements with near-duplicate videos. This project will make a major impact on social media mining, and open up a new research direction for topic discovery. The project's advances will bring economic/social benefits to Australia, where collaborative access of large amount of Web/media information is vital, for example, data sharing and management, broadcasting, advertising, opinion gathering, etc.
A theory of communicative practices within financial internet discussion site communities. This project aims to use online financial investment communities to identify factors that drive communication and influence knowledge co-creation, examine how systematic variations in these factors influence investor decision making, and develop a mid-range theory for explaining and predicting the influence of online communication patterns on individual decisions and market outcomes. By developing and vali ....A theory of communicative practices within financial internet discussion site communities. This project aims to use online financial investment communities to identify factors that drive communication and influence knowledge co-creation, examine how systematic variations in these factors influence investor decision making, and develop a mid-range theory for explaining and predicting the influence of online communication patterns on individual decisions and market outcomes. By developing and validating a new mid-range theory, initially in the financial investment context, this project will provide significant benefits, such as help to secure Australia’s place in a changing world through improved information flow.Read moreRead less
Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research ....Privacy-preserving cloud data mining-as-a-service. This project aims to explore practical privacy-preserving solutions for cloud data mining-as-a-service based on the Intel Software Guard Extensions (SGX) technology. The research addresses privacy concerns of users when outsourcing data mining needs to the cloud. These concerns have increased as more businesses evaluate data mining-as-an outsourced service due to lack of expertise or computation resources. The expected outcomes from the research will include new data privacy models, new privacy-preserving data mining algorithms, and a prototype of cloud data mining software. These will help businesses cut costs for data mining and privacy protection, and provide significant benefits toward helping Australia achieve its national cyber security strategy and potentially provide economic impact from commercialisation of new software technology for the industry partner.Read moreRead less
AI-driven Effective Query Formulation for Better Systematic Reviews. This project aims to develop novel AI-based search engine methods to make the creation of systematic reviews cheaper, faster and unbiased. Systematic reviews are the cornerstone for evidence-based decisions in clinical practice and government policy making. Given the pace new research is published at, it is unsustainable to manually conduct systematic reviews in the traditional manner, taking on average 2 years and $350K and be ....AI-driven Effective Query Formulation for Better Systematic Reviews. This project aims to develop novel AI-based search engine methods to make the creation of systematic reviews cheaper, faster and unbiased. Systematic reviews are the cornerstone for evidence-based decisions in clinical practice and government policy making. Given the pace new research is published at, it is unsustainable to manually conduct systematic reviews in the traditional manner, taking on average 2 years and $350K and becoming already outdated when published. The outcomes of this project will lead to systematic reviews of higher quality, while reducing their financial and temporal costs, providing significant benefits to organisations performing reviews and their funders, and to people impacted by decisions made from the reviews.Read moreRead less