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  1. A Process Model for Information Retrieval Context Learning and Knowledge Discovery.Harvey Hyman, Terry Sincich, Rick Will, Manish Agrawal, Balaji Padmanabhan & Warren Fridy - 2015 - Artificial Intelligence and Law 23 (2):103-132.
  • E-Discovery Revisited: The Need for Artificial Intelligence Beyond Information Retrieval. [REVIEW]Jack G. Conrad - 2010 - Artificial Intelligence and Law 18 (4):321-345.
    In this work, we provide a broad overview of the distinct stages of E-Discovery. We portray them as an interconnected, often complex workflow process, while relating them to the general Electronic Discovery Reference Model (EDRM). We start with the definition of E-Discovery. We then describe the very positive role that NIST’s Text REtrieval Conference (TREC) has added to the science of E-Discovery, in terms of the tasks involved and the evaluation of the legal discovery work performed. Given the critical nature (...)
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  • Afterword: Data, Knowledge, and E-Discovery. [REVIEW]David D. Lewis - 2010 - Artificial Intelligence and Law 18 (4):481-486.
    Research in Artificial Intelligence (AI) and the Law has maintained an emphasis on knowledge representation and formal reasoning during a period when statistical, data-driven approaches have ascended to dominance within AI as a whole. Electronic discovery is a legal application area, with substantial commercial and research interest, where there are compelling arguments in favor of both empirical and knowledge-based approaches. We discuss the cases for both perspectives, as well as the opportunities for beneficial synergies.
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  • Emerging AI & Law Approaches to Automating Analysis and Retrieval of Electronically Stored Information in Discovery Proceedings.Kevin D. Ashley & Will Bridewell - 2010 - Artificial Intelligence and Law 18 (4):311-320.
    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 (...)
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