{"id":5695,"date":"2024-01-01T16:42:55","date_gmt":"2024-01-01T16:42:55","guid":{"rendered":"https:\/\/icertpublication.com\/?page_id=5695"},"modified":"2024-01-03T07:18:22","modified_gmt":"2024-01-03T07:18:22","slug":"application-of-machine-learning-algorithms-in-predictive-legal-analytics","status":"publish","type":"page","link":"https:\/\/icertpublication.com\/index.php\/sodh-sari-vol-3-issue-1\/application-of-machine-learning-algorithms-in-predictive-legal-analytics\/","title":{"rendered":"Application Of Machine Learning Algorithms In Predictive Legal Analytics"},"content":{"rendered":"\t\t
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APPLICATION OF MACHINE LEARNING ALGORITHMS IN PREDICTIVE LEGAL ANALYTICS<\/span><\/p>

Ganapathy, Venkatasubramanian<\/span><\/p>

Faculty in Auditing Department, Southern India Regional Council of the Institute of Chartered Accountants of India (SIRC of ICAI), Chennai, Tamil Nadu, Bharat<\/span><\/p>


<\/b><\/p>

Introduction<\/span><\/p>

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 interventions. <\/span><\/p>



<\/b><\/p>

Impact Statement<\/span><\/p>


<\/b><\/p>

This research paper on the Application of Machine Learning Algorithms in Predictive Legal Analytics marks a groundbreaking advancement in legal practice. By harnessing the capabilities of machine learning, the study introduces a paradigm shift in legal decision-making. The implementation of sophisticated algorithms enables accurate prediction of case outcomes, risk assessment, and strategic optimization. This transformative approach not only enhances the efficiency of legal processes but also has far-reaching implications for resource allocation, cost reduction, and improved access to justice. The research addresses ethical considerations, ensuring responsible integration of machine learning in the legal domain. With profound implications for legal professionals, policymakers, and marginalized individuals seeking justice, this paper pioneers the way forward in leveraging technology to augment the fairness and efficacy of legal systems.<\/span><\/p>


<\/b><\/p>

About Author<\/span><\/p>

VENKATASUBRAMANIAN GANAPATHY<\/span><\/p>

Objective: Career Growth in the teaching profession with academic excellence and pursuit of further<\/span><\/p>

Qualifications and research.<\/span><\/p>

Academic Profile:<\/span><\/p>

\uf0d8 M.Phil (Commerce) from The Quaide Milleth College for Men- University of Madras-<\/span><\/p>

Ist Class- (2015-2016).<\/span><\/p>

\uf0d8 B.Ed \u2013 IGNOU, New Delhi- Distance Mode- 1 st Class \u2013 December 2009.<\/span><\/p>

\uf0d8 M.Com \u2013 Annamalai University \u2013 Distance Mode- 1 st Class \u2013 May 1995.<\/span><\/p>

\uf0d8 D.P.C.S. (Data Preparation and Computer Software) \u2013 NCVT Course \u2013Sri Ramakrishna<\/span><\/p>

Mission Computer Centre, Chennai \u2013 1 st Class \u2013 April 1993.<\/span><\/p>

\uf0d8 B.Com \u2013 St. Joseph\u2019s College (Autonomous), Trichy \u2013 Bharathidasan University \u2013 1 st<\/span><\/p>

Class \u2013 April 1990.<\/span><\/p>

\uf0d8 ICWA Inter (Group II) \u2013 December 1993.<\/span><\/p>


<\/b><\/p>

Academic Experience: 18 + Years<\/span><\/p>


<\/b><\/p>

Presently working as a Visiting Faculty in the SIRC of ICAI, Nungambakkam, Chennai,<\/span><\/p>

Tamil Nadu, Bharat<\/span><\/p>

Corporate Experience: 9 Years.<\/span><\/p>



<\/b><\/p>

REFERENCES<\/span><\/p>

  1. Predictive analytics in legal: 3 practical applications<\/span>.<\/span><\/p><\/li>

  2. Machine Learning with Legal Texts. https:\/\/www.cambridge.org\/core\/books\/artificial-intelligence-and-legal-analytics\/machine-learning-with-legal-texts\/7A55E8D261E3B5A89993AA59ED2F3601. Cambridge University Press.<\/span><\/p><\/li>

  3. Using machine learning to predict decisions of the European. – Springer<\/span>.<\/span><\/p><\/li>

  4. Unsupervised Simplification of Legal Texts. https:\/\/arxiv.org\/abs\/2209.00557<\/span><\/p><\/li>

  5. Machine Learning in legal industry \u2013 Potential, Pitfalls and how to make it work in real life. https:\/\/www.lexology.com\/library\/detail.aspx?g=ae37792e-eea3-40a1-9d6d-e764444c3fdf<\/span><\/p><\/li>

  6. Naveen, N., & Bhatia, A. (2023). Need of Machine Learning to predict Happiness: A Systematic review. <\/span>Edumania-An International Multidisciplinary Journal<\/span>, <\/span>01<\/span>(02), 306\u2013335. <\/span>https:\/\/doi.org\/10.59231\/edumania\/8991<\/span><\/a><\/p><\/li>

  7. Kumar, A. (2023). Promoting youth involvement in environmental sustainability for a sustainable Future. <\/span>Edumania-An International Multidisciplinary Journal<\/span>, <\/span>01<\/span>(03), 261\u2013278. <\/span>https:\/\/doi.org\/10.59231\/edumania\/9012<\/span><\/a><\/p><\/li><\/ol>


    <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

    APPLICATION OF MACHINE LEARNING ALGORITHMS IN PREDICTIVE LEGAL ANALYTICS Ganapathy, Venkatasubramanian Faculty in Auditing Department, Southern India Regional Council of the Institute of Chartered Accountants of India (SIRC of ICAI), Chennai, Tamil Nadu, Bharat Introduction Machine learning (ML) is a branch of artificial intelligence that enables computers to learn from data and make predictions based […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":5395,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"no-sidebar","site-content-layout":"page-builder","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"disabled","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-5695","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/pages\/5695","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/comments?post=5695"}],"version-history":[{"count":7,"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/pages\/5695\/revisions"}],"predecessor-version":[{"id":5767,"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/pages\/5695\/revisions\/5767"}],"up":[{"embeddable":true,"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/pages\/5395"}],"wp:attachment":[{"href":"https:\/\/icertpublication.com\/index.php\/wp-json\/wp\/v2\/media?parent=5695"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}