Automatic Legal Text Summarisation: Experiments with Summary Structuring

Ben Hachey, Claire Grover

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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 naïve 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.
Original languageEnglish
Title of host publicationThe Tenth International Conference on Artificial Intelligence and Law, Proceedings of the Conference, June 6-11, 2005, Bologna, Italy
PublisherACM
Pages75-84
Number of pages10
ISBN (Print)1-59593-081-7
DOIs
Publication statusPublished - 2005

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