LABDT (Lexi AdaBoost Decision Tree): An Approach for Legal Outcome Prediction Fusing Lexical, Semantic, and Similarity-based features Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.1007/s44196-025-01003-2
Legal outcome prediction is a complex task due to the nuanced vocabulary and reasoning embedded in judicial documents. This study proposes LABDT (Lexi AdaBoost Decision Tree), a novel hybrid framework that integrates lexical features (TF-IDF), semantic embeddings (Sentence-BERT), and similarity-based metrics for robust and interpretable legal decision classification. The model addresses class imbalance through SMOTE and reduces feature dimensionality via principal component analysis (PCA). LABDT was evaluated on a real-world dataset of approximately 18,000 cases from the Federal Court of Australia case records, spanning eight outcome classes. The results demonstrate that LABDT outperforms traditional and state-of-the-art classifiers with an accuracy of 92%, precision of 91%, recall of 91%, and F1-score of 91%. Notably, it achieved highly accurate classification on certain outcome classes like ‘approved’ and ‘related’. LABDT offers a superior balance between predictive performance and model interpretability compared to baseline models. The system’s explainable design and high classification reliability position it as a viable tool for AI-driven legal analytics and judicial decision support.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s44196-025-01003-2
- https://link.springer.com/content/pdf/10.1007/s44196-025-01003-2.pdf
- OA Status
- gold
- References
- 44
- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4415810430Canonical identifier for this work in OpenAlex
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https://doi.org/10.1007/s44196-025-01003-2Digital Object Identifier
- Title
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LABDT (Lexi AdaBoost Decision Tree): An Approach for Legal Outcome Prediction Fusing Lexical, Semantic, and Similarity-based featuresWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-11-03Full publication date if available
- Authors
-
Santanu Kumar Sahoo, Avinash Samantra, Chinmaya Kumar Mohapatra, Biswajit Swain, Zulfiqar Ali, Ghulam MuhammadList of authors in order
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https://doi.org/10.1007/s44196-025-01003-2Publisher landing page
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https://link.springer.com/content/pdf/10.1007/s44196-025-01003-2.pdfDirect link to full text PDF
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goldOpen access status per OpenAlex
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0Total citation count in OpenAlex
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