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Field of Research : Text Processing
Field of Research : Computational Linguistics
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  • Funded Activity

    Special Research Initiatives - Grant ID: SR0354513

    Funder
    Australian Research Council
    Funding Amount
    $20,000.00
    Summary
    The Computational Processing of Human Language. Language is what makes us distinctly human; consequently, language attracts interest from many fields of research, particularly linguistics, psychology, and cognitive science. Moreover, language is the primary medium for the storage and dissemination of knowledge, a fact that has drawn many computer scientists to attempt to process, analyse and understand language. This network will bridge the many disciplines that are concerned with language, ex .... The Computational Processing of Human Language. Language is what makes us distinctly human; consequently, language attracts interest from many fields of research, particularly linguistics, psychology, and cognitive science. Moreover, language is the primary medium for the storage and dissemination of knowledge, a fact that has drawn many computer scientists to attempt to process, analyse and understand language. This network will bridge the many disciplines that are concerned with language, explore new ways in which computational models inform our understanding of human languages, and exploit new opportunities for applying theories of language in the development of human language technologies.
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    Funded Activity

    Discovery Projects - Grant ID: DP0453131

    Funder
    Australian Research Council
    Funding Amount
    $330,000.00
    Summary
    Ask the Net: Intelligent Natural Language Learning. Natural Language Processing (NLP) has progressed rapidly using corpus-based machine learning techniques. However, corpus development costs cause a ?data bottleneck? which prevents systems from reaching human competence. This project overcomes the difficulties of creating huge corpora by employing the innate language ability of untrained contributors. We will show how to automatically select and present examples, containing informative lingui .... Ask the Net: Intelligent Natural Language Learning. Natural Language Processing (NLP) has progressed rapidly using corpus-based machine learning techniques. However, corpus development costs cause a ?data bottleneck? which prevents systems from reaching human competence. This project overcomes the difficulties of creating huge corpora by employing the innate language ability of untrained contributors. We will show how to automatically select and present examples, containing informative linguistic structures, which are most beneficial for training NLP systems. These examples will be analysed by many contributors whose responses will be automatically collated into corpora. Huge corpora are vital to emerging language technologies for managing textual information in the global economy.
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    Funded Activity

    Discovery Projects - Grant ID: DP0449928

    Funder
    Australian Research Council
    Funding Amount
    $135,000.00
    Summary
    A Layered Controlled Natural Language for Knowledge Representation. In this research project we will develop a controlled natural language for knowledge representation that has the potential to bridge the gap between fragments of natural language and formal languages. This controlled language will be based on a variety of increasing sophisticated layers, each building upon those below it by providing enhancements in expressive power. Sentences of the controlled language will be unambiguously tra .... A Layered Controlled Natural Language for Knowledge Representation. In this research project we will develop a controlled natural language for knowledge representation that has the potential to bridge the gap between fragments of natural language and formal languages. This controlled language will be based on a variety of increasing sophisticated layers, each building upon those below it by providing enhancements in expressive power. Sentences of the controlled language will be unambiguously translatable into a corresponding formal language. Anyone who can read and write English can immediately use the controlled language with the help an intelligent text editor. This technology will make it possible for non-specialists to write problem specifications in terms of the application domain without the need to formally encode the information.
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    Funded Activity

    Discovery Projects - Grant ID: DP0450750

    Funder
    Australian Research Council
    Funding Amount
    $290,000.00
    Summary
    A scalable and portable question-answering system. The current availability of large volumes of free text digitally stored demands the development of methodologies that can automatically find specific answers to user questions about this "unstructured" information. The goal of this project is to develop a scalable portable and domain-independent real-time natural-language question-answering system that explores the logical contents of the text. To achieve this we will fuse current approaches to .... A scalable and portable question-answering system. The current availability of large volumes of free text digitally stored demands the development of methodologies that can automatically find specific answers to user questions about this "unstructured" information. The goal of this project is to develop a scalable portable and domain-independent real-time natural-language question-answering system that explores the logical contents of the text. To achieve this we will fuse current approaches to question answering with approaches that look at the logical contents of the questions and answer candidates. A central part of the project will be the characterisation of the optimal logical forms, the determination of efficient methods to create and store sentence logical forms of potentially large volumes of text, and the treatment of difficult questions by incorporating summarisation and text generation techniques.
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    Funded Activity

    Discovery Projects - Grant ID: DP1097291

    Funder
    Australian Research Council
    Funding Amount
    $362,000.00
    Summary
    Parsing the web: Exploiting redundancy to understand language. This project will automatically learn the grammatical structure of language by exploiting redundancy of facts, like 'Mozart was born in 1756', from a trillion words of web text. These facts will be used to understand more complex sentences. This will enable smart information use of text with grammatical information for large-scale information access for the first time. This project will strengthen Australia's world-class expertise, .... Parsing the web: Exploiting redundancy to understand language. This project will automatically learn the grammatical structure of language by exploiting redundancy of facts, like 'Mozart was born in 1756', from a trillion words of web text. These facts will be used to understand more complex sentences. This will enable smart information use of text with grammatical information for large-scale information access for the first time. This project will strengthen Australia's world-class expertise, providing opportunities for future researchers in this area. Our expanded C&C tools and trillion word corpus will be used by academics, companies and governments, in Australia and internationally, aiding applications including financial surveillance and fraud detection.
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    Funded Activity

    Discovery Projects - Grant ID: DP0665973

    Funder
    Australian Research Council
    Funding Amount
    $240,000.00
    Summary
    Exploring Scientific Information with Advanced New Search Tools. The rapidly growth of scientific literature in many fields makes finding information a challenge. For example, biologists produce over 1 million articles each year. Existing search tools have only limited success satisfying the demands of scientists' queries. This project will deliver intelligent e-research assistants capable of answering scientists' questions directly rather than returning a list of documents. This will allow scie .... Exploring Scientific Information with Advanced New Search Tools. The rapidly growth of scientific literature in many fields makes finding information a challenge. For example, biologists produce over 1 million articles each year. Existing search tools have only limited success satisfying the demands of scientists' queries. This project will deliver intelligent e-research assistants capable of answering scientists' questions directly rather than returning a list of documents. This will allow scientists to more efficiently exploit the literature enabling them to be more innovative and productive. This technology is applicable where ever finding facts in large volumes of text is critical, e.g. analysing surveillance material. Advanced search tools will have considerable academic and industrial impact.
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