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manually conduct systematic reviews in the traditional manner, taking on average 2 years and $350K and becoming already outdated when published.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
Discovery Early Career Researcher Award - Grant ID: DE180101579
Funder
Australian Research Council
Funding Amount
$346,446.00
Summary
Searching when the stakes are high: better health decisions from search engines. This project aims to help people make better health decisions from search engines by improving the information that search queries return. Google is utilised by 80 per cent of Australians to search health symptoms, despite evidence showing that many often find incorrect and unreliable health information. This project expects to provide new understanding about why and how people fail to find useful health information ....Searching when the stakes are high: better health decisions from search engines. This project aims to help people make better health decisions from search engines by improving the information that search queries return. Google is utilised by 80 per cent of Australians to search health symptoms, despite evidence showing that many often find incorrect and unreliable health information. This project expects to provide new understanding about why and how people fail to find useful health information. Expected outcomes of this project include new models and methods for evaluating high-stakes search and new search technologies to help people find and recognise high quality information to make better health decisions. This should provide significant benefits to Australian health consumers and the healthcare system.Read moreRead less
QualA-D: a quality aware query engine for next generation data integration systems. This project will address the growing diversity of the web/user community by developing new approaches for data integration that incorporate data quality requirements such as data currency, completeness and coverage. First-of-breed quality aware query system is expected to be developed that will assist in improving user experience and satisfaction.
Architectural practice in postwar Queensland (1945-1975): building and interpreting an oral history archive. This project will document the histories of Queensland's postwar architects. It will produce a new digital research resource on Queensland architecture and an exhibition which will explore the role of climate, place, innovation and sustainability in Queensland's postwar architecture.
Scalable Cross-Media Hashing for Searching Heterogeneous Data Sources. This project aims to use novel indexing and search approaches to realise the value of multimedia data. The ever-increasing availability and heterogeneity of multimedia data are calling for new approaches to search information across different media types and data sources. This project aims to enable accurate and real-time cross-media searches from billions of multimedia objects collected from various media sources by tackling ....Scalable Cross-Media Hashing for Searching Heterogeneous Data Sources. This project aims to use novel indexing and search approaches to realise the value of multimedia data. The ever-increasing availability and heterogeneity of multimedia data are calling for new approaches to search information across different media types and data sources. This project aims to enable accurate and real-time cross-media searches from billions of multimedia objects collected from various media sources by tackling the heterogeneity and scalability issues. Expected outcomes include scalable cross-media hashing techniques to capture implicit correlations existing in heterogeneous data and embed high-dimensional features into short binary codes; new binary code indexing and ranking schemes to further improve search speed and quality; and a large-scale cross-media system to evaluate methods and demonstrate the practical value.Read moreRead less
Realising the value of mobile videos with context awareness. Innovative approaches to analysing online video content and context will lead to new ways of interacting with video in the mobile world. This project will aim to develop real-time mobile systems for enabling rich and highly dynamic digital video experiences through context-aware indexing, retrieval and consumption of mobile videos.
Discovery Early Career Researcher Award - Grant ID: DE230101116
Funder
Australian Research Council
Funding Amount
$420,000.00
Summary
Detecting Key Concepts from Low-Quality Data for Better Decision. The project aims to develop data analytics techniques that aid better decision making in high-stake scenarios when data are less-trustable. While data-aided decision making has been widely used, less-trustable data may significantly distort the decisions made and hurt people impacted by these decisions. The outcome of this project expects to be a series of techniques covering data understanding and enhancement, model development a ....Detecting Key Concepts from Low-Quality Data for Better Decision. The project aims to develop data analytics techniques that aid better decision making in high-stake scenarios when data are less-trustable. While data-aided decision making has been widely used, less-trustable data may significantly distort the decisions made and hurt people impacted by these decisions. The outcome of this project expects to be a series of techniques covering data understanding and enhancement, model development and fitting, and novelty detection, to reduce the damage of less-trustable data. The research expects to benefit the people and companies impacted by data-aided decision making in cybersecurity, healthcare and financial fraud detection, providing risk-control services.Read moreRead less
Intelligent Image Retrieval from Distorted and Partial Queries for Rapid Mobile Identification of Pests Threatening Food and the Environment. Pests and diseases are major threats to the Australian food industry and environmental biosecurity. A rapid and mobile pest information retrieval system is critical to prevent a pest becoming established and devastating the region. However, automated insect image retrieval remains an unsolved challenge in the research community. This project addresses the ....Intelligent Image Retrieval from Distorted and Partial Queries for Rapid Mobile Identification of Pests Threatening Food and the Environment. Pests and diseases are major threats to the Australian food industry and environmental biosecurity. A rapid and mobile pest information retrieval system is critical to prevent a pest becoming established and devastating the region. However, automated insect image retrieval remains an unsolved challenge in the research community. This project addresses the fundamental problem of distorted and partial image query in cluttered background in order to achieve pest identification at a much earlier on-site stage. The success of this research will not only make a technical breakthrough towards retrieving objects with movable body parts, but also revolutionise the current pest detection and monitoring process.Read moreRead less
An integrative and distributed data management and workflow framework for e-research in biomedical imaging. This project will develop new tools for neuroimaging research: (i) efficient distributed infrastructure and workflow capabilities and (ii) semantic tools using existing ontological frameworks and specific neuroimaging ontologies.
These new capabilities will significantly enhance the productivity of neuroimaging research.
Digital noticeboards for remote Aboriginal communities: bringing web 2.0 participation to non-western cultures with low English and technical literacy. Remote Aboriginal communities suffer from geographic and cultural isolation. Web 2.0 offers a solution yet is ill-suited to traditional collective cultures, those with low English and technical literacy, and the poor. This project will produce novel public web-enabled touchscreen noticeboards and table tops suited to traditional cultures.