Сравнение методов

	Прогнозирование судебных решений	Географическое профилирование
Область	Криминалистика	Криминалистика
Семейство	Process / pipeline	Process / pipeline
Год появления	2017	1994
Автор метода	Daniel Katz	David Canter
Тип	Computational law and judicial decision prediction method	Geographic and spatial analytics method
Основополагающий источник	Katz, D. M., Bommarito, M. J., & Blackman, J. (2017). A general approach for predicting the behavior of the Supreme Court of the United States. PLOS One, 12(4), e0174698.	Canter, D. V., & Hammond, L. (1994). Picking up the pieces: The identification of glass sources in forensic enquiries. Journal of Forensic Sciences, 39(4), 1018-1034.
Другие названия	court outcome prediction, judicial decision prediction, legal AI forecasting	spatial crime analysis, crime hotspot mapping
Связанные	3	3
Сводка	Legal judgment prediction is a machine learning approach that forecasts court decisions and judicial outcomes based on case features, legal precedent, and judicial characteristics. Pioneered by Daniel Katz and colleagues in 2017 with their celebrated U.S. Supreme Court prediction model, this method applies supervised learning to large datasets of digitized court decisions to identify patterns in how judges decide cases. Legal judgment prediction has since expanded to appellate courts, trial courts, and international tribunals, enabling legal professionals to anticipate case outcomes and make strategic litigation decisions.	Geographic profiling is a spatial analysis method used in forensic investigation to locate offenders based on the locations of their crimes. Developed by David Canter in 1994, it combines geostatistics, probability theory, and crime pattern analysis to identify high-probability crime origin zones. The method has been widely adopted in law enforcement agencies across North America and Europe.