APPLICATION OF MACHINE LEARNING ALGORITHMS IN PREDICTIVE LEGAL ANALYTICS

Shodh Sari-An International Multidisciplinary Journal Pub Date : 2024-01-01 DOI:10.59231/sari7675

Venkatasubramanian Ganapathy

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Abstract

Machine learning (ML) is a branch of artificial intelligence that enables computers to learn from data and make predictions based on patterns and statistics. ML applied to various domains, such as natural language processing, computer vision, and recommender systems. One of the emerging applications of ML is in the field of legal analytics, which aims to provide insights and guidance for legal professionals and stakeholders. Predictive legal analytics is a subfield of legal analytics that focuses on using ML to predict the outcomes of legal disputes, such as court cases, arbitrations, or negotiations. Predictive legal analytics can help lawyers and judges to assess the potential legal consequences of their actions, to align their decisions with past precedents, to identify the best strategies for resolving conflicts, and to improve the efficiency and quality of justice delivery. Predictive legal analytics can also help clients and policy makers to understand the legal risks and opportunities involved in their situations, to make informed decisions before initiating or pursuing a legal action, and to evaluate the impact of legal reforms and interventio

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机器学习算法在预测性法律分析中的应用

机器学习（ML）是人工智能的一个分支，它能让计算机从数据中学习，并根据模式和统计数据进行预测。机器学习应用于多个领域，如自然语言处理、计算机视觉和推荐系统。人工智能的新兴应用之一是法律分析领域，其目的是为法律专业人士和利益相关者提供见解和指导。预测性法律分析是法律分析的一个子领域，侧重于使用 ML 预测法律纠纷（如法庭案件、仲裁或谈判）的结果。预测性法律分析可以帮助律师和法官评估其行为的潜在法律后果，使其决策与以往的先例保持一致，确定解决冲突的最佳策略，并提高司法服务的效率和质量。预测性法律分析还能帮助客户和政策制定者了解其所处环境的法律风险和机遇，在发起或采取法律行动之前做出明智的决定，并评估法律改革和干预措施的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Shodh Sari-An International Multidisciplinary Journal

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