Tag Archives: Statistical methods in legal informatics

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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Schilling: Field of Forces: Strategic Interdependence in Legislative Behavior

Emily U. Schilling of the University of Iowa presented a paper entitled Field of Forces: Interdependence in Legislative Decision Making, 26 April 2014 at the New Faces in Political Methodology conference, sponsored by the Penn State Quantitative Social Science Initiative, … Continue reading

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Ruhl and Katz: How Complex is the Law, and How Complex Should It Be?

Professor Dr. J. B. Ruhl of Vanderbilt University and Professor Dr. Daniel Martin Katz of Michigan State University and the ReInvent Law Laboratory, presented a paper entitled How Complex is the Law, and How Complex Should It Be?, at SEAL … Continue reading

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Chou et al.: Automated prediction of construction contract disputes with hybrid AI model

Professor Dr. Jui-Sheng Chou, Professor Dr. Min-Yuan Cheng, Yu-Wei Wu, and Anh-Duc Pham have published Optimizing parameters of support vector machine using fast messy genetic algorithm for dispute classification, Expert Systems with Applications, 41, 3955–3964 (2014). Here is the abstract: … Continue reading

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Surden: Machine Learning and Law

Professor Harry Surden of the University of Colorado has published Machine Learning and Law, Washington Law Review, 89, 87-115 (2014). Here is the abstract: This Article explores the application of machine learning techniques within the practice of law. Broadly speaking … Continue reading

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Yavorosky: Predicting the effect of public comments on administrative rules

Bart Mykolas Yavorosky has posted the full text of his Ph.D. dissertation entitled Comparing Apples: Predicting the effect of public comments on administrative rules (Virginia Tech, 2014). Here is the abstract: This dissertation addresses three questions about administrative rulemaking: Do … Continue reading

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Zorn: Decision Making in the Federal Judicial Hierarchy: Data Toward A Theory

Professor Dr. Christopher Zorn of Penn State University has posted slides of his presentation entitled Decision Making in the Federal Judicial Hierarchy: Data Toward A Theory, given 1 March 2014 at CAPR 2014: Annual Conference of the Center for American … Continue reading

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