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ICAIL
2005
ACM

Automatic Legal Text Summarisation: Experiments with Summary Structuring

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Automatic Legal Text Summarisation: Experiments with Summary Structuring
We describe a set of experiments using machine learning techniques for the task of extractive summarisation. The research is part of a summarisation project for which we use a corpus of judgments of the UK House of Lords. We present classification results for na¨ıve Bayes and maximum entropy and we explore methods for scoring the summary-worthiness of a sentence. We present sample output from the system, illustrating the utility of rhetorical status information, which provides a means for structuring summaries and tailoring them to different types of users. Keywords Automatic summarisation, Discourse, Natural language, Machine learning
Ben Hachey, Claire Grover
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where ICAIL
Authors Ben Hachey, Claire Grover
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