AI-Based Legal Document Summarization for Judicial Assistance
DOI:
https://doi.org/10.63345/Keywords:
Legal Document Summarization, Judicial Assistance, Machine Learning, Extractive Summarization, Transformer Models, Legal InformaticsAbstract
The exponential growth of legal documents, judgments, case briefs, and statutory texts poses a major challenge to the judiciary and legal practitioners worldwide. Legal professionals often face significant difficulty in manually analyzing voluminous records within constrained timelines, leading to delays in justice delivery. Artificial Intelligence (AI)-based legal document summarization has emerged as a transformative approach that leverages Natural Language Processing (NLP), Machine Learning (ML), and Deep Learning (DL) techniques to extract essential information from lengthy documents and generate concise, contextually relevant summaries.
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