Abstract
This article provides an overview of, and thematic justification for, the special issue of the journal of Artificial Intelligence and Law entitled “E-Discovery”. In attempting to define a characteristic “AI & Law” approach to e-discovery, and since a central theme of AI & Law involves computationally modeling legal knowledge, reasoning and decision making, we focus on the theme of representing and reasoning with litigators’ theories or hypotheses about document relevance through a variety of techniques including machine learning. We also identify two emerging techniques for enabling users’ document queries to better express the theories of relevance and connect them to documents: social network analysis and a hypothesis ontology.
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Ashley, K.D., Bridewell, W. Emerging AI & Law approaches to automating analysis and retrieval of electronically stored information in discovery proceedings. Artif Intell Law 18, 311–320 (2010). https://doi.org/10.1007/s10506-010-9098-4
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DOI: https://doi.org/10.1007/s10506-010-9098-4