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Introduction

Natural Language Generation (NLG) is a subfield of artificial intelligence and computational linguistics that focuses on the automatic generation of human-readable text or speech from data. In recent years, NLG has gained significant attention in various industries, including e-commerce, where it is used to automatically generate product descriptions, reviews, and other content.

Automated product descriptions are essential for online retailers as they help in improving search engine optimization, enhancing user experience, and increasing sales. However, creating engaging and informative product descriptions manually for a large number of products can be time-consuming and costly. NLG offers a solution to this problem by automating the process of generating product descriptions using advanced algorithms and natural language processing techniques.

This thesis aims to investigate the use of NLG for automated product descriptions and evaluate its effectiveness in improving the quality and efficiency of product description generation. The research will focus on developing a prototype NLG system for generating product descriptions and conducting user studies to assess its performance and user satisfaction.

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
2.1 Overview of NLG
2.2 NLG Techniques
2.3 Applications of NLG in E-commerce
2.4 Challenges of NLG for Automated Product Descriptions
2.5 Approaches to NLG for Automated Product Descriptions
2.6 Evaluation Metrics for NLG Systems
2.7 User Perception of NLG-Generated Content
2.8 Ethical Considerations in NLG for Product Descriptions
2.9 Current Trends in NLG Research
2.10 Gaps in Existing Literature

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection
3.3 NLG System Development
3.4 User Study Design
3.5 Data Analysis Techniques
3.6 Ethical Considerations
3.7 Limitations of Research Methodology
3.8 Validity and Reliability of Findings

Chapter 4: Discussion of Findings
4.1 Evaluation of NLG System Performance
4.2 User Satisfaction with NLG-Generated Product Descriptions
4.3 Comparison with Manual Product Descriptions
4.4 Impact on SEO and Conversion Rates
4.5 Implications for E-commerce Industry
4.6 Recommendations for Future Research
4.7 Practical Implementation Considerations

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Contributions of the Study
5.3 Implications for Practice
5.4 Limitations of the Study
5.5 Recommendations for Further Research
5.6 Conclusion

Thesis Overview on Natural Language Generation for Automated Product Descriptions

Natural Language Generation (NLG) is a rapidly evolving field in artificial intelligence and computational linguistics that has vast applications in automated content generation. In the context of e-commerce, NLG plays a crucial role in generating product descriptions to enhance user experience and drive sales. This thesis focuses on investigating the use of NLG for automated product descriptions and evaluating its effectiveness in improving the quality and efficiency of content generation.

Chapter 1 provides an introduction to NLG for automated product descriptions, outlining the background of the study, problem statement, objectives, limitations, scope, significance, and structure of the thesis. Chapter 2 presents a comprehensive literature review on NLG techniques, applications in e-commerce, challenges, evaluation metrics, user perception, ethical considerations, current trends, and gaps in existing literature.

Chapter 3 discusses the research methodology, including research design, data collection, NLG system development, user study design, data analysis techniques, ethical considerations, limitations, and validity of findings. Chapter 4 presents a detailed discussion of the research findings, including the evaluation of the NLG system performance, user satisfaction, comparison with manual descriptions, impact on SEO and conversion rates, implications for the e-commerce industry, recommendations, and practical implementation considerations.

Chapter 5 concludes the thesis by summarizing the findings, highlighting the contributions of the study, discussing implications for practice, identifying limitations, offering recommendations for further research, and providing a conclusion. Overall, this thesis aims to advance the understanding of NLG for automated product descriptions and contribute to the development of innovative solutions in the e-commerce domain.

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