Approaches to text mining arguments from legal cases

This chapter describes recent approaches using text-mining to automatically profile and extract arguments from legal cases. We outline background context and motivations. We then turn to consider issues related to the construction and composition of a corpus of legal cases. We show how a context-free grammar can be used to extract arguments, and how ontologies and natural language processing can identify complex information such as case factors and participant roles. The results bring us closer to the automatic identification of arguments in text.

Publication year:2010

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