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Introduction

Text summarization and question answering are two important techniques in the field of natural language processing that can greatly benefit legal research. Legal research involves analyzing large amounts of text from court cases, statutes, and legal documents to extract relevant information and provide valuable insights. However, manually reading and extracting information from these texts can be time-consuming and error-prone.

Text summarization techniques aim to automatically generate concise summaries of longer texts, making it easier for researchers to quickly grasp the key points and extract relevant information. Question answering systems, on the other hand, allow users to ask specific questions about legal texts and receive precise answers, saving time and effort in the research process.

This thesis aims to explore the use of text summarization and question answering techniques in the context of legal research. By developing and evaluating models that can effectively summarize legal texts and answer legal questions, this research seeks to improve the efficiency and accuracy of legal researchers in extracting relevant information from large volumes of legal documents.

Table of Contents

Chapter 1: Introduction
– 1.1 Introduction
– 1.2 Background of study
– 1.3 Problem Statement
– 1.4 Objective of study
– 1.5 Limitation of study
– 1.6 Scope of study
– 1.7 Significance of study
– 1.8 Structure of the Thesis
– 1.9 Definition of terms

Chapter 2: Literature Review
– Review of text summarization techniques
– Review of question answering techniques
– Applications of text summarization in legal research
– Applications of question answering in legal research
– Challenges and limitations of text summarization for legal research
– Challenges and limitations of question answering for legal research
– Comparative analysis of existing text summarization and question answering models
– Evaluation metrics for text summarization and question answering in legal research
– Recent advancements in text summarization and question answering for legal research
– Future directions and research opportunities

Chapter 3: Research Methodology
– Data collection and preprocessing
– Text summarization model design
– Question answering model design
– Model training and evaluation
– Experimental setup
– Performance metrics
– Data analysis techniques
– Ethical considerations

Chapter 4: Discussion of Findings
– Evaluation results of text summarization model
– Evaluation results of question answering model
– Comparison of models
– Interpretation of results
– Implications for legal research
– Limitations of the study
– Future research directions

Chapter 5: Conclusion and Summary
– Summary of key findings
– Contributions of the study
– Practical implications
– Recommendations for future research
– Conclusion

Thesis Overview

Text summarization and question answering are two important techniques in natural language processing that can greatly benefit legal research. This thesis aims to explore the use of these techniques in the context of legal research to improve the efficiency and accuracy of extracting relevant information from legal texts.

Chapter 1 provides an introduction to the research, including background information, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of terms. Chapter 2 presents a comprehensive literature review on text summarization and question answering techniques, their applications in legal research, challenges, comparative analysis, evaluation metrics, recent advancements, and future directions.

Chapter 3 outlines the research methodology, including data collection, preprocessing, model design, training, evaluation, experimental setup, performance metrics, data analysis, and ethical considerations. Chapter 4 discusses the findings of the study, including evaluation results of the text summarization and question answering models, comparison of models, interpretation of results, implications for legal research, limitations, and future research directions.

Finally, Chapter 5 presents the conclusion and summary of the thesis, summarizing key findings, contributions, practical implications, recommendations for future research, and conclusion. Overall, this thesis aims to contribute to the field of legal research by exploring the use of text summarization and question answering techniques to enhance the efficiency and accuracy of extracting relevant information from legal texts.

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