New approaches to interactive sessional search for complex tasks. This project aims to develop new tools and techniques to improve the accuracy and speed of search and data analytics for complex information tasks. There are currently no publicly available search engines which support users engaged in complex interactive search, or that allow searchers to fully control their own data and privacy. Fundamental research advances, based on understanding real user behaviour and search needs will have ....New approaches to interactive sessional search for complex tasks. This project aims to develop new tools and techniques to improve the accuracy and speed of search and data analytics for complex information tasks. There are currently no publicly available search engines which support users engaged in complex interactive search, or that allow searchers to fully control their own data and privacy. Fundamental research advances, based on understanding real user behaviour and search needs will have an impact on important academic, industrial, and government domains, including virtual assistants, health care (clinical decision support), precision medicine, eDiscovery, crime prevention, and detailed socio-economic evaluations.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140100275
Funder
Australian Research Council
Funding Amount
$392,979.00
Summary
Beyond keyword search for ranked document retrieval. This project will develop novel approaches to efficient and effective ranked text retrieval using a new class of rank-aware algorithms derived from self-indexes. These algorithms can support complex statistical calculations on the fly. Efficient algorithm design for big data is an increasingly important problem as energy costs continue to soar and can now exceed hardware costs for big data consumers such as Google. In this project, two importa ....Beyond keyword search for ranked document retrieval. This project will develop novel approaches to efficient and effective ranked text retrieval using a new class of rank-aware algorithms derived from self-indexes. These algorithms can support complex statistical calculations on the fly. Efficient algorithm design for big data is an increasingly important problem as energy costs continue to soar and can now exceed hardware costs for big data consumers such as Google. In this project, two important problems in web search are explored: real-time indexing and long-form query answering. Using self-index algorithms, this project presents a road map to move beyond simple keyword-based ranked document retrieval, thus allowing us to efficiently meet more demanding information needs of users in the next decade.Read moreRead less
Constraints in XML Schema Integration. This project will produce worldwide leading technologies for designing XML data integration system. With the technologies, the well designed integration systems will be able store data with rich semantics and thus provide accurate and understandable information to users. In this way, Australia and communities will be benefited both financially and informatively. The research of this project will also add to the research reputation of Australia in data integ ....Constraints in XML Schema Integration. This project will produce worldwide leading technologies for designing XML data integration system. With the technologies, the well designed integration systems will be able store data with rich semantics and thus provide accurate and understandable information to users. In this way, Australia and communities will be benefited both financially and informatively. The research of this project will also add to the research reputation of Australia in data integration areas. At the same time, the knowledge capacity of Australia on data integration will be enlarged which further improves frontier research activities in the area. Through the research of the project, PhD students will be trained.Read moreRead less
Searching Cohesive Subgraphs in Big Attributed Graph Data. The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and ....Searching Cohesive Subgraphs in Big Attributed Graph Data. The availability of big attributed graph data brings great opportunities for realizing big values of data. Making sense of such big attributed graph data finds many applications, including health, science, engineering, business, environment, etc. A cohesive subgraph, one of key components that captures the latent properties in a graph, is essential to graph analysis. This project aims to invent effective models of cohesive subgraphs and efficient algorithms for searching and monitoring cohesive subgraphs in big and dynamic attributed graphs from both structure and attribute perspectives. The methods, techniques, and prototype systems developed in this project can be deployed to facilitate the smart use of big graph data across the nation. Read moreRead less
Modelling and Searching Cohesive Groups over Heterogeneous Graphs . Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for differen ....Modelling and Searching Cohesive Groups over Heterogeneous Graphs . Heterogeneous information networks (HINs) contain richer structural and semantic information represented as different types of objects and links. Searching cohesive groups from HINs finds many applications and also brings challenges at both conceptual and technical levels. This project aims to investigate the effective modelling of cohesive groups that take both homogeneous and heterogeneous information into account for different applications and devise efficient algorithms for searching and monitoring those cohesive groups based on different models. The methods, techniques, and evaluation systems developed in this project can be deployed to facilitate the smart use of heterogeneous information networks across the nation.Read moreRead less
Data retrieval from massive information structures. Information search is an essential tool. But most current services regard the data as unstructured collections of independent documents, free of context. Next-generation search applications, such as over social networks, or corporate websites, or XML data sets, must account for the inherent relationships between data items, and must allow the efficient inclusion of search context. Queries should favour semantically local data, giving results th ....Data retrieval from massive information structures. Information search is an essential tool. But most current services regard the data as unstructured collections of independent documents, free of context. Next-generation search applications, such as over social networks, or corporate websites, or XML data sets, must account for the inherent relationships between data items, and must allow the efficient inclusion of search context. Queries should favour semantically local data, giving results that depend on the perceived state of the querier. This project will develop indexing and search techniques for massive structured data sets. The new search methods will incorporate theoretical advances and will be experimentally validated using industry-standard open-source distributed systems.Read moreRead less
On Effectively Answering Why and Why-not Questions in Databases. While the performance and functionality of database systems have gained dramatic improvement, research on improving usability still remains far behind, which results in huge cost of technical support to organisations. This project aims to improve the usability of database systems by effectively answering users' why and why-not questions on query results. This project will invent a novel and generalised model for expressing both the ....On Effectively Answering Why and Why-not Questions in Databases. While the performance and functionality of database systems have gained dramatic improvement, research on improving usability still remains far behind, which results in huge cost of technical support to organisations. This project aims to improve the usability of database systems by effectively answering users' why and why-not questions on query results. This project will invent a novel and generalised model for expressing both the why and why-not questions, efficient strategies for answering questions for complex queries and databases, and novel solutions to scenarios that involve multiple queries. The project will contribute greatly to the fundamental research in query refinement and deliver significant impact on related technology development. Read moreRead less
Using Past Queries for Fast and Accurate Web Searching. Searching the entire Internet, or a company web site, has become a vital task for modern organisations. While there has been significant research into improving search engines through using web pages themselves, very little attention has been paid to improving web search by exploiting the vast numbers of queries that users submit to search engines each day. This project will use state of the art compression and algorithmic techniques to imp ....Using Past Queries for Fast and Accurate Web Searching. Searching the entire Internet, or a company web site, has become a vital task for modern organisations. While there has been significant research into improving search engines through using web pages themselves, very little attention has been paid to improving web search by exploiting the vast numbers of queries that users submit to search engines each day. This project will use state of the art compression and algorithmic techniques to improve the speed and accuracy of web search using data gleaned from millions of Internet queries (provided under agreement by Microsoft). Improving search engines will have a direct benefit to many Australian industries, and support the government's priority area of "smart information use".Read moreRead less
Making Spatiotemporal Data More Useful: An Entity Linking Approach. This project aims to establish a methodology for spatiotemporal entity linking by utilising object movement traces to support database integration and data quality management for the next-generation of data where spatiotemporal attributes are ubiquitous. It expects to develop a novel entity linking paradigm for automatic, efficient and reliable spatiotemporal data integration together with a new data privacy study in this contex ....Making Spatiotemporal Data More Useful: An Entity Linking Approach. This project aims to establish a methodology for spatiotemporal entity linking by utilising object movement traces to support database integration and data quality management for the next-generation of data where spatiotemporal attributes are ubiquitous. It expects to develop a novel entity linking paradigm for automatic, efficient and reliable spatiotemporal data integration together with a new data privacy study in this context. Expected outcome include new database technologies for data signature generation and similarity-based search, and improved location data privacy protection methods. This project should provide significant benefits to all areas where high quality spatiotemporal data fusion is essential to meaningful data analysis.Read moreRead less
Identifying and Tracking Influential Events in Large Social Networks. This project aims to invent a novel model and techniques for identifying and tracking influential events in large and dynamic social networks in real time. The proposed model would take into account the structure and content of social networks, and the influence of events. The project also plans to develop efficient strategies for identifying and tracking events in large and dynamic social network environments based on the mod ....Identifying and Tracking Influential Events in Large Social Networks. This project aims to invent a novel model and techniques for identifying and tracking influential events in large and dynamic social networks in real time. The proposed model would take into account the structure and content of social networks, and the influence of events. The project also plans to develop efficient strategies for identifying and tracking events in large and dynamic social network environments based on the model, In particular, the project plans to investigate flexible social network query methods to make users’ event search easy. Finally the project plans to build an evaluation system to demonstrate the efficiency of the algorithms and effectiveness of the model.Read moreRead less