Emerging AI & Law approaches to automating analysis and retrieval of electronically stored information in discovery proceedings |
| |
Authors: | Kevin D. Ashley Will Bridewell |
| |
Affiliation: | 1. School of Law, University of Pittsburgh, Pittsburgh, PA, 15260, USA 2. Cognitive Systems Laboratory, Center for the Study of Language and Information, Stanford University, Stanford, CA, 94305, USA
|
| |
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. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|