Monitoring social events for user online behaviour analytics. This project aims to investigate the influence of public attention on steering user online behaviour. The exponential growth of online behaviour data makes online behaviour analytics increasingly important in social, commercial and political environments, but existing methods rely on user profiles only. The project will unify external social events with user profiles for behaviour analytics, and develop approaches for event database i ....Monitoring social events for user online behaviour analytics. This project aims to investigate the influence of public attention on steering user online behaviour. The exponential growth of online behaviour data makes online behaviour analytics increasingly important in social, commercial and political environments, but existing methods rely on user profiles only. The project will unify external social events with user profiles for behaviour analytics, and develop approaches for event database indexing, event-influenced behaviour modelling and prediction. The success of this project is expected to enhance users’ online experience and improve e-commerce’s market value.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.
Deep attribute-aware hashing for cross retrieval. This project aims to enable individuals, industries and governments, to freely access vital and linked information carried in different media types from different sources by developing a deep attribute-aware framework that embeds heterogeneous features into a shared data space to achieve effective and efficient cross system information retrieval. With the proliferation of heterogeneous data sources, there is an urgent need to enable search and re ....Deep attribute-aware hashing for cross retrieval. This project aims to enable individuals, industries and governments, to freely access vital and linked information carried in different media types from different sources by developing a deep attribute-aware framework that embeds heterogeneous features into a shared data space to achieve effective and efficient cross system information retrieval. With the proliferation of heterogeneous data sources, there is an urgent need to enable search and retrieval across different media types and domains. The framework developed by the project uses deep learning methods to develop meaningful image attributes to positively bridge the modality gap and the domain gap when hash functions are affixed to data. This project will significantly advance the research of multimedia retrieval, and benefit a series of related research problems whenever heterogeneous multimedia data are involved in their applications.Read moreRead less
Synergising multimedia content understanding with social data analysis. This project aims to develop novel approaches to explore synergies within big social multimedia data from both social and multimedia perspective. It provides individuals, groups, and businesses the ability to tap into the wisdom of crowds to enlarge knowledge base, enhance user experience, understand the pulse of crowds and make informed decision.
Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop ne ....Privacy Preserving Data Sharing in Electronic Health Environment. This project aims to improve access to electronic health data (EHD) while still ensuring patient privacy. EHD can provide important information for medical research and health-care resource allocations. However, data sharing in electronic health environments is challenging because of the privacy concerns of customers. Large-scale unauthorised access from internal staff has been reported in Medicare. This project aims to develop new privacy-preserving algorithms on EHD database federations, which can provide efficient data access yet block inside attacks. It will significantly improve the data available for medical research, while reducing the cost of EHD system management and providing visualised decision supports to medical staff and the government health resource planners.Read moreRead less
Real-time Event Detection, Prediction, and Visualization for Emergency Response. This project proposes novel end-to-end methods for real-time recognition and prediction of real-world events, leading to timely response to emergencies such as disease outbreaks and natural disasters, as well as prevention of crime, security breaches and the like. It will develop new techniques to quickly detect and predict events by incorporating adaptive learning and probabilistic models, and address fusion and sc ....Real-time Event Detection, Prediction, and Visualization for Emergency Response. This project proposes novel end-to-end methods for real-time recognition and prediction of real-world events, leading to timely response to emergencies such as disease outbreaks and natural disasters, as well as prevention of crime, security breaches and the like. It will develop new techniques to quickly detect and predict events by incorporating adaptive learning and probabilistic models, and address fusion and scalability factors to handle vast collections of heterogeneous data. An event surveillance system prototype will be developed to incorporate the findings of the research with tools to visualise and describe events.Read moreRead less
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.
Fusion of digital microscopy and plain text reports for automated analysis. The project aims to develop advanced computer-aided analytics systems with the goal to improve the workflow and automation in the pathology industry. Improvements will be achieved by fusing information from both digital images and plain text medical reports. In collaboration with a partner organisation, the project team will field trial the new analytics systems against traditional pathology tests to evaluate both effica ....Fusion of digital microscopy and plain text reports for automated analysis. The project aims to develop advanced computer-aided analytics systems with the goal to improve the workflow and automation in the pathology industry. Improvements will be achieved by fusing information from both digital images and plain text medical reports. In collaboration with a partner organisation, the project team will field trial the new analytics systems against traditional pathology tests to evaluate both efficacy and reliability. In addition, the project is also aimed to construct a large digital slide databank which will aid training and education. The expected outcome of the project is to perform existing tasks cheaper and more efficiently. Read moreRead less
Market segmentation methodology: attacking the 'Too Hard' basket. Businesses embrace market segmentation to identify and target clients. However, poor segmentation analysis leads to poor segment choice. This project will develop tools to improve segmentation analysis and will test the resulting tools in tourism, foster care and climate change mitigating behaviours, and produce usable, transferable recommendations.