Paper Key : IRJ************190
Author: Prathamesh Bhoge
Date Published: 04 Feb 2025
Abstract
Legal documents often contain complex and dense information that can be time-consuming and difficult to understand. To tackle these challenges, this paper introduces an automatic summarization of legal texts can provide a valuable solution by extracting key information and presenting it in a more accessible format. This paper presents a approach to the summarization of legal documents. We propose a hybrid model that uses natural language processing (NLP) methods to identify and summarize critical legal concepts of third party websites. Our approach uses pre-trained language models that are adapted to a collection of legal documents mainly Terms and Conditions(T&C), helping the system better understand legal terms and structure. We tested the model using a dataset of labeled legal documents, and the results show that it produces more relevant and clearer summaries compared to traditional methods. The proposed system can make it easier to understand legal documents like T&C. By making T&C documents easier to understand, our approach can improve the user experience, especially on online platforms where users often deal with these agreements.
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