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  1. Argumentation mining.Raquel Mochales & Marie-Francine Moens - 2011 - Artificial Intelligence and Law 19 (1):1-22.
    Argumentation mining aims to automatically detect, classify and structure argumentation in text. Therefore, argumentation mining is an important part of a complete argumentation analyisis, i.e. understanding the content of serial arguments, their linguistic structure, the relationship between the preceding and following arguments, recognizing the underlying conceptual beliefs, and understanding within the comprehensive coherence of the specific topic. We present different methods to aid argumentation mining, starting with plain argumentation detection and moving forward to a more structural analysis of the detected (...)
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  • Automatically classifying case texts and predicting outcomes.Kevin D. Ashley & Stefanie Brüninghaus - 2009 - Artificial Intelligence and Law 17 (2):125-165.
    Work on a computer program called SMILE + IBP (SMart Index Learner Plus Issue-Based Prediction) bridges case-based reasoning and extracting information from texts. The program addresses a technologically challenging task that is also very relevant from a legal viewpoint: to extract information from textual descriptions of the facts of decided cases and apply that information to predict the outcomes of new cases. The program attempts to automatically classify textual descriptions of the facts of legal problems in terms of Factors, a (...)
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  • Identification of rhetorical roles for segmentation and summarization of a legal judgment.M. Saravanan & B. Ravindran - 2010 - Artificial Intelligence and Law 18 (1):45-76.
    Legal judgments are complex in nature and hence a brief summary of the judgment, known as a headnote , is generated by experts to enable quick perusal. Headnote generation is a time consuming process and there have been attempts made at automating the process. The difficulty in interpreting such automatically generated summaries is that they are not coherent and do not convey the relative relevance of the various components of the judgment. A legal judgment can be segmented into coherent chunks (...)
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  • Extractive summarisation of legal texts.Ben Hachey & Claire Grover - 2006 - Artificial Intelligence and Law 14 (4):305-345.
    We describe research carried out as part of a text summarisation project for the legal domain for which we use a new XML corpus of judgments of the UK House of Lords. These judgments represent a particularly important part of public discourse due to the role that precedents play in English law. We present experimental results using a range of features and machine learning techniques for the task of predicting the rhetorical status of sentences and for the task of selecting (...)
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