---
title: Data Augmentation for Legal Cases
url: https://www.ml-quant.com/papers/repec/spr-trosos-v-18-y-2024-i-1-d-10-1007-s12626-024-00158-2/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:spr:trosos:v:18:y:2024:i:1:d:10.1007_s12626-024-00158-2
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs12626-024-00158-2%3Bh%3Drepec%3Aspr%3Atrosos%3Av%3A18%3Ay%3A2024%3Ai%3A1%3Ad%3A10.1007_s12626-024-00158-2
featured: 2024-04-24
citations: unknown
topic: ML & AI Methods
---


# Data Augmentation for Legal Cases

The article explores the application of machine learning in the COLIEE competition, using data augmentation to enhance the analysis of legal documents.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Flink.springer.com%2F10.1007%2Fs12626-024-00158-2%3Bh%3Drepec%3Aspr%3Atrosos%3Av%3A18%3Ay%3A2024%3Ai%3A1%3Ad%3A10.1007_s12626-024-00158-2
- Identifier: RePEc:spr:trosos:v:18:y:2024:i:1:d:10.1007_s12626-024-00158-2
- Released: 2024-04-24
- First featured: Quant Letter No. 46 (2024-04-24): https://www.ml-quant.com/issues/2024-04-24/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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