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Introduction

Natural language generation (NLG) is a subfield of artificial intelligence that focuses on the automatic generation of human-like text from structured data. NLG has various applications, one of which is automated product review summarization. With the increasing number of online reviews for products, it has become challenging for consumers to sift through all the information and make informed purchasing decisions. Automated product review summarization using NLG can help summarize large volumes of reviews into concise and informative summaries for consumers.

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

Chapter 2: Literature Review
2.1 Overview of natural language generation
2.2 Applications of NLG in automated product review summarization
2.3 Previous studies on product review summarization using NLG
2.4 Techniques used in NLG for summarization
2.5 Challenges in automated product review summarization
2.6 Evaluation metrics for product review summarization
2.7 User perspectives on automated summaries
2.8 Ethical considerations in automated summarization
2.9 Future trends in NLG for product review summarization
2.10 Summary of literature review

Chapter 3: Research Methodology
3.1 Research design
3.2 Data collection
3.3 Data preprocessing
3.4 NLG model selection
3.5 Evaluation methodology
3.6 Ethical considerations
3.7 Validation process
3.8 Potential limitations
3.9 Data analysis techniques

Chapter 4: Discussion of Findings
4.1 Overview of findings
4.2 Comparison of NLG models
4.3 Evaluation of automated summaries
4.4 User feedback on summaries
4.5 Ethical implications of automated summarization
4.6 Recommendations for future research
4.7 Implications for industry
4.8 Limitations of the study

Chapter 5: Conclusion and Summary
5.1 Summary of key findings
5.2 Contributions to the field
5.3 Recommendations for future research
5.4 Conclusion

Thesis Overview on Natural Language Generation for Automated Product Review Summarization

Automated product review summarization using natural language generation (NLG) is a cutting-edge technology that aims to provide consumers with concise and informative summaries of product reviews. This thesis investigates the application of NLG in automated product review summarization, with a focus on evaluating different NLG models and techniques for generating summaries.

Chapter 1 provides an introduction to the research topic, outlining the background of the study, problem statement, objectives, limitations, scope, significance, and structure of the thesis. Chapter 2 conducts a comprehensive literature review on NLG, its applications in product review summarization, previous studies, techniques, challenges, evaluation metrics, user perspectives, ethical considerations, and future trends.

Chapter 3 details the research methodology, including research design, data collection, preprocessing, NLG model selection, evaluation methodology, ethical considerations, validation process, potential limitations, and data analysis techniques. Chapter 4 discusses the findings of the research, comparing NLG models, evaluating automated summaries, analyzing user feedback, discussing ethical implications, providing recommendations, and outlining limitations.

Chapter 5 presents the conclusion and summary, summarizing key findings, discussing contributions to the field, suggesting future research directions, and concluding the thesis. This thesis aims to contribute to the advancement of NLG in automated product review summarization and provide valuable insights for researchers, practitioners, and industry professionals in the field.

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