Towards High-Order Structure Search on Large-Scale Graphs. High-order structure search over large-scale graphs has many applications including cybersecurity, crime detection, social media, marketing recommendation, and public health. The project aims to lay the scientific foundations and develop novel computing techniques for efficiently conducting structure search. The outcomes include novel computing paradigms, algorithms, indexing, incremental computation, and distributed solutions. The succe ....Towards High-Order Structure Search on Large-Scale Graphs. High-order structure search over large-scale graphs has many applications including cybersecurity, crime detection, social media, marketing recommendation, and public health. The project aims to lay the scientific foundations and develop novel computing techniques for efficiently conducting structure search. The outcomes include novel computing paradigms, algorithms, indexing, incremental computation, and distributed solutions. The success of the project will directly contribute to the scientific foundation of Big Data computation. It will also contribute to the development of local industry involving cybersecurity, social media based recommendation, network management, and E-business.Read moreRead less
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
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.
Cost efficient scheduling of big data application workflows on cloud through information correlation. Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling rese ....Cost efficient scheduling of big data application workflows on cloud through information correlation. Information correlation in and between big data application workflows scheduled on the cloud can help to significantly reduce overall scheduling costs by avoiding the execution of many correlated workflow activities. This project aims to systematically investigate such correlation for cost efficient scheduling. The expected outcomes are: establishing information correlation based scheduling research and practical solutions for this important cloud and big data research area; benefiting key big data application areas on the cloud, such as hospitals, insurance companies and government information services; and helping to maintain Australia at the forefront of cloud and big data research with innovative industry applications.Read moreRead less
From Data to Artefact: a Key Ingredient in Service Interoperation. Supporting service interoperation in the e-Business environment is crucial in automating business transactions across organisation boundaries. If no proper mechanism is in place, business delays, failures, and serious disputes can occur. This project will explore new avenues to this long-standing and challenging problem by providing an artefact framework to model and manage business collaboration. Given this project's unique pers ....From Data to Artefact: a Key Ingredient in Service Interoperation. Supporting service interoperation in the e-Business environment is crucial in automating business transactions across organisation boundaries. If no proper mechanism is in place, business delays, failures, and serious disputes can occur. This project will explore new avenues to this long-standing and challenging problem by providing an artefact framework to model and manage business collaboration. Given this project's unique perspective and approaches that are directly applicable to existing enterprise systems, there is a strong potential for its results to lead to a new generation of e-Business design and management, advance the knowledge base of the discipline and yield high returns to the Australian service society and IT industry.Read moreRead less
Pattern Discovery of Discriminating Behaviour Associated with Hidden Communities. A sound understanding of discriminating behaviour in hidden communities, e.g. market manipulation, is essential for effective intervention and prevention. This project will deliver novel and workable algorithms and tools for modelling and pattern discovery of such behaviour. This will safeguard Australia by tackling crucial business and social issues like abnormal trading, online crime and terrorism, thereby enhanc ....Pattern Discovery of Discriminating Behaviour Associated with Hidden Communities. A sound understanding of discriminating behaviour in hidden communities, e.g. market manipulation, is essential for effective intervention and prevention. This project will deliver novel and workable algorithms and tools for modelling and pattern discovery of such behaviour. This will safeguard Australia by tackling crucial business and social issues like abnormal trading, online crime and terrorism, thereby enhancing public confidence, compliance and security in both the economy and society, by preventing and reducing economic and social impact. It will create skills and outcomes to further Australia's leadership in managing emerging data mining challenges and applications, and will deepen collaboration with eminent researchers worldwide.Read moreRead less
Deep Pattern Mining for Brain Graph Analysis: A Data Mining Perspective. This project brings together experts in the fields of data mining and cognitive neuroscience. This project aims to develop new data analytics tools, algorithms, and models to combine complex multi-source neuroimage brain data and non-imaging data, to explore the interplays among these different data structures and identify novel functional patterns from complex brain graph structures. The research undertaken in this project ....Deep Pattern Mining for Brain Graph Analysis: A Data Mining Perspective. This project brings together experts in the fields of data mining and cognitive neuroscience. This project aims to develop new data analytics tools, algorithms, and models to combine complex multi-source neuroimage brain data and non-imaging data, to explore the interplays among these different data structures and identify novel functional patterns from complex brain graph structures. The research undertaken in this project expects to provide practical data analysis approaches and establish the theoretical foundations for data mining with multiple sources of brain data.Read moreRead less