Discovery Early Career Researcher Award - Grant ID: De120102900
Funder
Australian Research Council
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.
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.
Improved syntactic and semantic analysis for natural language processing. This project aims to improve the accuracy of syntactic and semantic analysis of natural language for automatic extraction of meaning from text. Many data mining and information extraction applications rely on syntactic and semantic analysis. Current analysis approaches are limited because they require expensive manually-labelled data. The project plans to develop new indirectly-supervised approaches to overcome this labell ....Improved syntactic and semantic analysis for natural language processing. This project aims to improve the accuracy of syntactic and semantic analysis of natural language for automatic extraction of meaning from text. Many data mining and information extraction applications rely on syntactic and semantic analysis. Current analysis approaches are limited because they require expensive manually-labelled data. The project plans to develop new indirectly-supervised approaches to overcome this labelled data bottleneck. By integrating information from large text corpora and structured databases, the project aims to minimise the reliance on manually-labelled data for training natural language processing systems. Automatic methods for syntactic and semantic analysis would have a wide range of applications in extracting information from large collections of unstructured data, such as hospital patient records or social media.Read moreRead less
Talking about place: tapping human knowledge to enrich national spatial data sets. Place descriptions are a common way for people to describe a location, but no current tools are smart enough to understand them. Emergency call centres are risking lives, users of navigation or web services are frustrated and addressing these problems costs billions of dollars per year. This project comes with a novel, interdisciplinary approach to automatically interpret human place descriptions and will develop ....Talking about place: tapping human knowledge to enrich national spatial data sets. Place descriptions are a common way for people to describe a location, but no current tools are smart enough to understand them. Emergency call centres are risking lives, users of navigation or web services are frustrated and addressing these problems costs billions of dollars per year. This project comes with a novel, interdisciplinary approach to automatically interpret human place descriptions and will develop novel methods to capture placenames with their meaning for smarter databases and automatic interpretation procedures. This acquired knowledge will be an important step forward for Australia's data custodians and users. Australia's location information industry will gain a significant advantage on a highly competitive global market.Read moreRead less
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.