Text Mining for the Analysis of Legal Texts-Reference-Cited by-同舟云学术

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Text Mining for the Analysis of Legal Texts

Published:2022-09-26 Issue: Volume: Page:
ISSN:
Container-title:2022 12th International Conference on Advanced Computer Information Technologies (ACIT)
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Author:

Kovalchuk Olha¹,Banakh Serhiy²,Masonkova Mariia³,Berezka Kateryna¹,Mokhun Serhii⁴,Fedchyshyn Olha⁴

Affiliation:

1. West Ukrainian National University,Department of Applied Mathematics,Ternopil,UKRAINE

2. West Ukrainian National University,Criminal Law and Process Department,Ternopil,UKRAINE

3. Kherson State Maritime Academy,International Affairs Department,Kherson,UKRAINE

4. Ternopil Volodymyr Hnatiuk National Pedagogical University,Department of Physics and Mathematics,Ternopil,UKRAINE

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9912736/9912739/09913169.pdf?arnumber=9913169

Reference17 articles.

1. Text Classification Using Data Mining;kamruzzaman;International Conference of Communications and Information Technology,2005

2. Automatic Text Classification: A Technical Review

3. Decision tree model for classification of fake and genuine banknotes using SPSS

4. Investigate the Performance of Document Clustering Approach Based on Association Rules Mining

5. Ontology-based knowledge recognition in service-oriented virtual research environments

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1. ‘LAWGIC’: An Application for Automated Legal Document Classification and Retrieval;Journal of Electronics and Informatics;2024-06

2. Implementation of innovative information technologies in judicial proceedings: organizational and legal aspect;Revista Amazonia Investiga;2024-04-30

3. Identifying the Causes of Ship Collisions Accident Using Text Mining and Bayesian Networks;Elektronika ir Elektrotechnika;2023-12-13

4. Survival Analysis Models for Estimating and Predicting the Risks of Confession of Criminal Defendants;2023 13th International Conference on Advanced Computer Information Technologies (ACIT);2023-09-21

5. Prediction Machine Learning Models on Propensity Convicts to Criminal Recidivism;Information;2023-03-03

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