Practical applications of a classified taxonomy for predicting the progress of court cases
This presentation explores the earnings within the realization of the Legal Case Law Analytics and Modeling (LCAM) project, which applies AI technologies and statistical modeling to large-scale civil judicial data in Ukraine. It demonstrates applications for the developend taxonomy for legal cases scenario predictions. The presentation was delivered by Vitaliy Miroshnychenko from Taras Shevchenko National University of Kyiv at the Legal Case Analytics & Modeling (LCAM): Mathematics meets Law workshop, organized by Linnaeus University and Taras Shevchenko National University of Kyiv on 18–21 August 2026 within the LCAM: Legal Case Law Analytics & Modeling (2024–2026) project, funded by the Swedish Institute (SI).
Authors
- Yuliya Stepanovna Mishura (ORCID: https://orcid.org/0000-0002-6877-1800)
- Vitaliy Miroshnychenko (ORCID: https://orcid.org/0009-0003-9799-8902)
- Iryna Izarova (ORCID: https://orcid.org/0000-0002-1909-7020)
- Yurii D. PRYTYKA (ORCID: https://orcid.org/0000-0001-5992-1144)
- Yuliia Hartman (ORCID: https://orcid.org/0000-0002-5637-8358)
- Vitaliy Golomoziy (ORCID: https://orcid.org/0000-0002-3174-9781)
Institutions
- Taras Shevchenko National University of Kyiv (UA)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-24
- DOI
- https://doi.org/10.5281/zenodo.22936384
- Primary Topic
- Artificial Intelligence in Law
- Type
- article
- Field-Weighted Citation Impact
- 0.00