Effective and Efficient Keyword Search in Relational Databases. Effective and efficient management of information, including textual information, is at the heard of ICT objectives and requirements global wide. The project aims to be of unique value to vitually all Australian industries by providing easier and better information access to their business data. The research conducted in this project will position Australia as one of the leaders in the database and information retrieval research. Th ....Effective and Efficient Keyword Search in Relational Databases. Effective and efficient management of information, including textual information, is at the heard of ICT objectives and requirements global wide. The project aims to be of unique value to vitually all Australian industries by providing easier and better information access to their business data. The research conducted in this project will position Australia as one of the leaders in the database and information retrieval research. The project outcomes in the form of algorithms and systems will provide powerful solutions that are applicable to many Australian and international organisations. It will will also encourage more ICT within Australia and worldwide.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100509
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Effective Recommendation for Web of Things. This project seeks to generate novel techniques for the efficient recommendation of things by the smart use of information generated from the ‘Internet of things’. The ‘Internet of things’ will connect billions of physical things over the web, which will offer exciting capabilities to improve the quality of human lives. This project focuses on effective recommendation of things of interest, and aims to develop new techniques and a set of software tools ....Effective Recommendation for Web of Things. This project seeks to generate novel techniques for the efficient recommendation of things by the smart use of information generated from the ‘Internet of things’. The ‘Internet of things’ will connect billions of physical things over the web, which will offer exciting capabilities to improve the quality of human lives. This project focuses on effective recommendation of things of interest, and aims to develop new techniques and a set of software tools for effectively and proactively discovering and recommending things. The result of this project may underpin applications (eg smart cities) that will contribute to Australian society and the national economy.Read moreRead less
Efficient Techniques for Mining Exceptional Patterns. This research will develop totally new techniques for exceptional pattern discovery that are useful for deeper understanding data mining and capturing the hidden interactions (class-bridge rules and out-expectation patterns) within data. This will enable Australian data marketers to access valuable implicit information that is contained in their data, but not currently accessible. The outcomes will keep Australia in the international leading ....Efficient Techniques for Mining Exceptional Patterns. This research will develop totally new techniques for exceptional pattern discovery that are useful for deeper understanding data mining and capturing the hidden interactions (class-bridge rules and out-expectation patterns) within data. This will enable Australian data marketers to access valuable implicit information that is contained in their data, but not currently accessible. The outcomes will keep Australia in the international leading edge and preserve its competitive status in preemptively defining the information market of tomorrow. To 'Frontier Technologies for Building and Transforming Australian Industries', discovering new exceptional patterns within data will lead to increased efficiency in Australian Industries.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100679
Funder
Australian Research Council
Funding Amount
$395,220.00
Summary
Real-time query processing over multi-dimensional uncertain data streams. Real-time query processing of multi-dimensional uncertain data streams is fundamental in many applications such as environmental monitoring and location based services. This project aims to develop effective techniques to explore the massive multi-dimensional uncertain data streams in real time. The project will develop, analyse, implement and evaluate novel indexing and query processing techniques to effectively and effic ....Real-time query processing over multi-dimensional uncertain data streams. Real-time query processing of multi-dimensional uncertain data streams is fundamental in many applications such as environmental monitoring and location based services. This project aims to develop effective techniques to explore the massive multi-dimensional uncertain data streams in real time. The project will develop, analyse, implement and evaluate novel indexing and query processing techniques to effectively and efficiently support a set of primitive queries including rank-based queries, dominance-based queries and proximity-based queries. The results of this project will be an important complement to the development of data stream systems and will bring considerable social, economic and technological benefits to Australia.Read moreRead less
Taming the uncertainty in trajectory data. This project aims to develop effective and efficient methods to manage large scale uncertain trajectory data. It provides individuals, business, government and social groups the ability to explore significant uncertain trajectories and their patterns, for important usages in location based services, logistic, transportation and tourism.
In-memory moving objects analytics for real-time business applications. This project aims to develop a novel computing foundation based on in-memory technologies to address significant challenges of big data and location-based business intelligence, building upon the well-recognised research excellence in spatiotemporal data management at the University of Queensland, and HANA, SAP's (Systems, Applications, Products in data processing) new in-memory analytics platform.
Efficient Strategies for Mining Negative Association Rules. Negative association rules (NAR) catch mutually-exclusive correlations
among items. They play important roles just as traditional association
rules (TAR) do. For example, in stock market surveillance based on alert logs, NARs detect which alerts are false. There are essential differences between mining TARs and NARs because NARs are hidden in infrequent itemsets. This research will develop efficient strategies for mining NARs in datab ....Efficient Strategies for Mining Negative Association Rules. Negative association rules (NAR) catch mutually-exclusive correlations
among items. They play important roles just as traditional association
rules (TAR) do. For example, in stock market surveillance based on alert logs, NARs detect which alerts are false. There are essential differences between mining TARs and NARs because NARs are hidden in infrequent itemsets. This research will develop efficient strategies for mining NARs in databases. These strategies are expected to be about ten times faster than existing ones. This project will deliver database-independent and high-performance mining algorithms for decision-making. The results can benefit Australian marketing and financial companies as well as health and security departments for smart information use.Read moreRead less
Multiple Data Source Discovery: Group Interaction Approach. This project will develop new technology and theory to identify and evaluate incomplete data. It will deliver a high-performance group-interaction based global pattern discovery system that enables decision-makers (like doctors) to access valuable implicit information that is contained in their data but not currently accessible. Mining group interactions will greatly extend the scope of pattern discovery and new product evaluation. The ....Multiple Data Source Discovery: Group Interaction Approach. This project will develop new technology and theory to identify and evaluate incomplete data. It will deliver a high-performance group-interaction based global pattern discovery system that enables decision-makers (like doctors) to access valuable implicit information that is contained in their data but not currently accessible. Mining group interactions will greatly extend the scope of pattern discovery and new product evaluation. The outcomes of the project will lead to better diagnostic decisions and will lead to increased efficiency in Australian Industries.Read moreRead less
Effective Techniques and Methodologies for Multi-Database Mining. This project develops a high-performance multi-database mining system. This project is significant because (1) it is imperative due to a great deal of multi-databases widely used in organizations; (2) it is difficult due to essential differences between mono- and multi-databases; (3) existing multi-database mining techniques are inadequate; and (4) the new mining strategies in this project can make a vast improvement of the abilit ....Effective Techniques and Methodologies for Multi-Database Mining. This project develops a high-performance multi-database mining system. This project is significant because (1) it is imperative due to a great deal of multi-databases widely used in organizations; (2) it is difficult due to essential differences between mono- and multi-databases; (3) existing multi-database mining techniques are inadequate; and (4) the new mining strategies in this project can make a vast improvement of the ability and performance of multi-database mining systems. The expected outcomes are: an application-independent database classification, a local instance analysis and a prototype system. These proposed techniques are innovative, effective and efficient in identifying novel patterns from multi-databases.Read moreRead less
Ontology-Based Group Pattern Discovery Systems for Mining Multiple Data Sources. This project will aim at the frontier technologies development for practical techniques in the context of real multiple-data-source mining systems, including stock data and e-business data analysis. It will bring Australian individuals and organizations (i) high quality information from multiple data sources and (ii) automatically pattern discovery systems for tackling the multiple data source problem. This will lea ....Ontology-Based Group Pattern Discovery Systems for Mining Multiple Data Sources. This project will aim at the frontier technologies development for practical techniques in the context of real multiple-data-source mining systems, including stock data and e-business data analysis. It will bring Australian individuals and organizations (i) high quality information from multiple data sources and (ii) automatically pattern discovery systems for tackling the multiple data source problem. This will lead to greatly enhance the international competition of Australian companies and significantly reduce investing risks. Read moreRead less