Tag Archives: Statistical methods in legal informatics

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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Parker-Stephen and Zorn: Predictive Analytics for Substantive and Operational Decisions in Law

Dr. Evan Parker-Stephen and Professor Dr. Christopher Zorn, both of Lawyer Metrics LLC, have posted slides of their presentation entitled Predictive Analytics for Substantive and Operational Decisions, given 26 February 2014 at the Forum on Legal Evolution, in New York … Continue reading

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Katz and Bommarito: Legal Analytics, Machine Learning, and Comments on the Status of Innovation in the Legal Industry

Professor Dr. Daniel Martin Katz of Michigan State University and the ReInvent Law Lab, and Michael J. Bommarito II, M.S.E., M.A., of Bommarito Consulting, have posted slides of their presentation entitled Legal Analytics, Machine Learning, and Some Comments on the … Continue reading

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Forum on Legal Evolution, NYC, 26 February 2014: Storify, tweets, and resources

The Forum on Legal Evolution was held 26 February 2014 in New York City. According to Ron Friedmann, the event was organized by Professor William Henderson, Professor Dr. Daniel Martin Katz, and Bruce MacEwen. The Twitter hashtag for the event … Continue reading

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Henderson and Zorn: Statistical analysis of lateral hiring by law firms, and explanations

Professor William Henderson of Indiana University and Professor Dr. Christopher Zorn of Penn State University have published Is Reliance on Lateral Hiring Destabilizing Firms?, American Lawyer, 3 February 2014. The article presents results of a statistical analysis of the lateral … Continue reading

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Mancuhan and Clifton: Combating discrimination using Bayesian networks

Koray Mancuhan and Professor Dr. Chris Clifton of Purdue University have published Combating discrimination using Bayesian networks, forthcoming in Artificial Intelligence and Law. Here is the abstract: Discrimination in decision making is prohibited on many attributes (religion, gender, etc…), but … Continue reading

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