Tag Archives: Statistical methods in legal informatics

Sim et al.: The Utility of Text: The Case of Amicus Briefs and the Supreme Court

Yanchuan Sim, Bryan Routledge, and Noah A. Smith presented a paper entitled The Utility of Text: The Case of Amicus Briefs and the Supreme Court, at New Directions in Text as Data 2014, held 10-11 October 2014 at Northwestern University … Continue reading

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Surden to speak on ‘Machine Learning Within Law’ at Stanford, October 9, 2014

Harry Surden of the University of Colorado is scheduled to give a presentation entitled Machine Learning Within Law, October 9, 2014 at Stanford Law School. Video of the presentation is available at: https://www.youtube.com/watch?v=sOLXOsiX0Qk The event is sponsored by CodeX: Stanford … Continue reading

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Legal informatics papers at ICFIS 2014

A number of papers on legal informatics, legal data analysis, or legal information were presented at ICFIS 2014: International Conference on Forensic Inference and Statistics, held 19-22 August 2014 in Leiden. The program is available at: https://dl.dropboxusercontent.com/u/6795661/ICFIS2014/program.html HT Bart Verheij

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Vlek et al.: Building Bayesian networks for legal evidence with narratives: A case study evaluation

Charlotte S. Vlek, Henry Prakken, Silja Renooij, and Bart Verheij, have published Building Bayesian networks for legal evidence with narratives: a case study evaluation, forthcoming in Artificial Intelligence and Law. Here is the abstract: In a criminal trial, evidence is … Continue reading

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Dolin: Inconsistency Robustness and the Law: A Random Walk

Ron Dolin of Stanford Law School has posted slides of his presentation entitled Inconsistency Robustness and the Law: A Random Walk, given at the conference, Inconsistency Robustness 2014, held 29-31 July 2014 at Stanford University. The presentation describes several types … Continue reading

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Katz, Bommarito, and Blackman: Predicting the Behavior of the Supreme Court of the United States: A General Approach

Daniel Martin Katz, Michael Bommarito, and Josh Blackman have posted a working paper entitled Predicting the Behavior of the Supreme Court of the United States: A General Approach. Here is the abstract: Building upon developments in theoretical and applied machine … Continue reading

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Katz and Bommarito’s research on measuring legal complexity is featured in Wired Science

Daniel Martin Katz and Michael Bommarito‘s paper, entitled Measuring the Complexity of the Law: The United States Code, is the focus of a new post by Samuel Arbesman at Wired Science: Measuring the Complexity of the Law. Here are excerpts … Continue reading

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