Grey literature, policy innovation and access to knowledge: realising the value of informal publishing. This project examines the growth of informal research publishing, 'grey literature' in Australia, and the policies and practices that shape it. The project will make recommendations for producers, collecting institutions and policy-makers on how to maximise the considerable social and cultural benefit of 'grey literature'.
Language engineering in the field: preserving 100 endangered languages in New Guinea. Efforts to preserve the world's endangered linguistic heritage are labour-intensive, and unable to keep up with the pace of language loss. This project investigates a new approach to language preservation, using techniques from language engineering, and leveraging the labour of mother-tongue speakers.
Biochemical text mining for advancing chemical and pharmaceutical knowledge. The project aims to develop novel natural language processing methods to find, extract and structure complex chemical reaction information in scientific literature. The project addresses a recognised bottleneck to efficiency in the drug discovery process, by enabling biochemical research results to be turned into actionable information. This has the potential to inform and accelerate development of effective drug treatm ....Biochemical text mining for advancing chemical and pharmaceutical knowledge. The project aims to develop novel natural language processing methods to find, extract and structure complex chemical reaction information in scientific literature. The project addresses a recognised bottleneck to efficiency in the drug discovery process, by enabling biochemical research results to be turned into actionable information. This has the potential to inform and accelerate development of effective drug treatments through the linking of relevant biochemical information. By delivering new methods that improve the compilation of knowledge about chemicals and drugs from textual information resources, the project hopes to enable faster drug discovery.Read moreRead less
Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business t ....Dialogue-to-Action:Towards A Self-Evolving Enterprise Intelligent Assistant. The project aims to develop a novel Self-Evolving Enterprise Intelligent Assistant (EIA) by leveraging the Chatbot-based dialogue technique to acquire information, infer user intentions, understand languages, and determine subsequent actions to take through Dialogue-to-Action modelling. This new generation EIA is equipped with Artificial Generalised Intelligence, with a broad skill set able to tackle multiple business tasks and handle fast-changing scenarios in business. The Self-Evolving EIA is a critical step on the path towards the future generation of EIA. Expected outcomes of this project are to develop adaptive EIA for Small and Medium Enterprise to improve their customer service quality.Read moreRead less
Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approa ....Automated assessment of data quality in biological knowledge resources. This project aims to develop methods for identifying poor quality data in biological databases. Research in biomedicine is underpinned by massive databases of biological data. Data quality is largely managed through manual curation, but automated methods to assess quality are critically needed. This project expects to develop a suite of computational tools for assessing biological data quality, utilising an innovative approach based on network analysis of database record connectivity. These tools will enable quantifying data quality at scale. Researchers, evidence-based decision-makers in biomedicine, and the analytical or predictive tools that use this data will make more reliable inferences and decisions.Read moreRead less
Spoken conversational search: contextual interactive techniques to support effective information search over a speech-only communication channel. This project will develop new techniques for effective information search using speech only, supporting improved information access for visually impaired people or in situations that require focused visual attention (e.g. driving). The techniques are based on a conversational approach to information search and presentation of results.
Discovery Early Career Researcher Award - Grant ID: DE120102900
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
WikiLinks: web-scale linking and fact extraction with Wikipedia. Wikipedia is the most popular web site for finding facts, but articles about local or specialist topics are often missing or unreliable. WikiLinks will use artificial intelligence to link names in text to corresponding Wikipedia articles, allowing us to automatically create and augment Wikipedia content by summarising existing material on the web.
Making human place knowledge digestible by computers. This project aims to develop the tools that will enable people to interact intuitively with computers about places and the relations between places. People understand their environment in a different way to computers; they think of places and their relations, while computers use coordinates and maps. People’s interaction with maps is cognitively costly and error-prone, which is becoming untenable in situations needing time-critical decision m ....Making human place knowledge digestible by computers. This project aims to develop the tools that will enable people to interact intuitively with computers about places and the relations between places. People understand their environment in a different way to computers; they think of places and their relations, while computers use coordinates and maps. People’s interaction with maps is cognitively costly and error-prone, which is becoming untenable in situations needing time-critical decision making. The project will revolutionise the design of information services where computers deal with humans and location in time-critical or stressful situations, including emergency calls, disaster response and local search queries. The uptake of this design by industry will lead to economic benefits as well as a safer society living in a smarter environment.Read moreRead less
Personalised topic modelling and sentiment analysis for enhanced information discovery over document streams. This project will develop personalised information discovery, navigation and management systems of online content for the creative industries, e.g. to help advertising agencies understand market trends, and enable designers to discover and analyse information relating to new product concepts.
Natural language processing for automated validation of protein databases. The project aims to use natural language processing and information retrieval to reconcile and improve sources of biological information. Biological research has produced vast volumes of information about proteins, captured in structured resources (databases) and unstructured documents. However, the accuracy of much of this information is questionable. The project proposes to develop methods to validate data and reduce th ....Natural language processing for automated validation of protein databases. The project aims to use natural language processing and information retrieval to reconcile and improve sources of biological information. Biological research has produced vast volumes of information about proteins, captured in structured resources (databases) and unstructured documents. However, the accuracy of much of this information is questionable. The project proposes to develop methods to validate data and reduce the dramatic inconsistencies in protein information resources by leveraging observed correlations and complementarity between them, and specifically through targeted fact extraction from the biomedical literature. These methods will be applied at scale across millions of published articles, to infer and validate functional information.Read moreRead less