Supreme court dialogue classification using machine learning models

Title

Supreme court dialogue classification using machine learning models

Creator

Joseph T.; Adiyillam V.

Description

Legal classification models help lawyers identify the relevant documents required for a study. In this study, the focus is on sentence level classification. To be more precise, the work undertaken focuses on a conversation in the supreme court between the justice and other correspondents. In the study, both the nae Bayes classifier and logistic regression are used to classify conversations at the sentence level. The performance is measured with the help of the area under the curve score. The study found that the model that was trained on a specific case yielded better results than a model that was trained on a larger number of conversations. Case specificity is found to be more crucial in gaining better results from the classifier. 2023 Institute of Advanced Engineering and Science. All rights reserved.

Source

International Journal of Electrical and Computer Engineering, Vol-13, No. 2, pp. 2350-2355.

Date

2023-01-01

Publisher

Institute of Advanced Engineering and Science

Subject

Legal classification model; Logistic classifier; Machine learning; Natural language processing; Nae Bayes model

Coverage

Joseph T., Department of Computer Science, Christ (Deemed to be University), Bengaluru, India; Adiyillam V., Department of Computer Science, Christ (Deemed to be University), Bengaluru, India

Rights

All Open Access; Gold Open Access; Green Open Access

Relation

ISSN: 20888708

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.11591/ijece.v13i2.pp2350-2355

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143883789&doi=10.11591%2fijece.v13i2.pp2350-2355&partnerID=40&md5=c95eba95b95d0ef8fed3a6a5ad5cf1ea