Tag Archives: Quantitative legal prediction

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. The event is sponsored by CodeX: Stanford Center for Legal Informatics, and is part of … Continue reading

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Do Robot Lawyers Dream of Billable Seconds? ILTA 2014 Program: Storify, links, and resources

A program entitled Do Robot Lawyers Dream of Billable Seconds? was held 21 August 2014 at ILTA 2014: International Legal Technology Association Annual Educational Conference, in Nashville, Tennessee, USA. The Website for the program does not appear to have a … 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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Stanford Symposium on Law and Rationality: Legal Trial, With and Without Mathematics, 30 May 2014: Links and resources

The 2014 Stanford Symposium on Law and Rationality, on the theme: Trial With and Without Mathematics: Legal, Philosophical, and Computational Perspectives, is scheduled to be held 30 May 2014, at Stanford Law School, in Stanford, California, USA. The conference is … Continue reading

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McGinnis and Pearce: The Great Disruption: How Machine Intelligence Will Transform the Role of Lawyers in the Delivery of Legal Services

Professor John O. McGinnis of Northwestern University and Professor Russell G. Pearce of Fordham University have published The Great Disruption: How Machine Intelligence Will Transform the Role of Lawyers in the Delivery of Legal Services, Fordham Law Review, 82, 3041-3066 … 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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