Enhancing Legal Guidance by Utilizing Natural Language Processing-Based Document Embeddings

Mukim, Tanmay Laxmikant (2024) Enhancing Legal Guidance by Utilizing Natural Language Processing-Based Document Embeddings. Masters thesis, Dublin, National College of Ireland.

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Abstract

The creation of a state-of-the-art recommendation framework for legal case study recommendations is examined in this corresponding work, which tends to utilize the four various types of Natural Language Processing (NLP) methods. Two different datasets, which mainly represent the legal citation data, are utilized in the implementation as well as the assessment of each of the models, which specifically comprise Word2Vec in combination with TF-IDF with Bidirectional Encoder Representations from Transformers (BERT), ALBERT together with DEBERTa. The specified main goal is to put forth a complex framework that can make recommendations for specific legal citations by utilizing the special advantages of these Natural Language Processing (NLP) methods accordingly. This specific research explores the effectiveness and comparative analysis of various Natural Language Processing (NLP) architectures, driven by the necessity for cutting-edge innovation in legal research. The implemented models are taught to execute the extraction of connotational significance from legal text together with understanding its subtleties by authorizing precisely with pertinent legal citation recommendations. A thorough evaluation of each specified Natural Language Processing (NLP) method’s capability to provide precise legal citations is one of the main conclusions this research draws. Additionally, to provide clarity on the evenness of the variations in the recommendations that are made because of the implementation of these corresponding four models, the research compares how comparable the implemented Natural Language Processing (NLP) methods are. In conclusion, by offering a solid foundation for the improvisation of a legal recommendation framework via the integration of several Natural Language Processing (NLP) procedures, this study advances different informative aspects in the legal sector.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Syed, Muslim Jameel UNSPECIFIED
Uncontrolled Keywords:	Legal Recommendation Framework; Natural Language Processing; Comparative Survey; Textual Similarity
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing K Law > K Law (General) > The Legal Profession
Divisions:	School of Computing > Master of Science in Artificial Intelligence
Depositing User:	Tamara Malone
Date Deposited:	04 Apr 2025 15:43
Last Modified:	04 Apr 2025 15:43
URI:	https://norma.ncirl.ie/id/eprint/7370

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