Natural Language Generation for Automated Content Creation – Complete Phd and Masters Thesis

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Introduction:

Natural Language Generation (NLG) is a field of artificial intelligence that focuses on the generation of human-like text from structured data. NLG is increasingly being used in various applications, including automated content creation, where it can be used to generate news articles, product descriptions, and other types of content. This thesis explores the use of NLG for automated content creation and its impact on the field of content generation.

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 Natural Language Generation
2.2 Applications of NLG in Content Creation
2.3 NLG Techniques and Models
2.4 Challenges and Limitations of NLG in Content Creation
2.5 NLG Evaluation Metrics
2.6 NLG Ethics and Bias
2.7 NLG in Marketing and Advertising
2.8 NLG in Journalism
2.9 NLG in E-commerce
2.10 Future Trends in NLG for Automated Content Creation

Chapter 3: Research Methodology
3.1 Research Design
3.2 Data Collection
3.3 NLG Model Selection
3.4 NLG Training and Evaluation
3.5 Data Preprocessing
3.6 Performance Metrics
3.7 Ethical Considerations
3.8 Research Limitations

Chapter 4: Discussion of Findings
4.1 NLG Performance Evaluation
4.2 Comparison of NLG Models
4.3 Impact of NLG on Content Creation
4.4 User Perspectives on NLG-generated Content
4.5 Ethical and Legal Implications
4.6 Recommendations for Future Research
4.7 Practical Applications of NLG in Content Creation
4.8 Limitations of the Study

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Contributions to the Field
5.3 Implications for Practice
5.4 Future Research Directions
5.5 Conclusion

Thesis Overview:

Natural Language Generation (NLG) for Automated Content Creation is a growing field that has the potential to revolutionize the way content is generated and consumed. This thesis investigates the use of NLG in automated content creation and its impact on various industries such as journalism, marketing, and e-commerce. The thesis begins with an introduction to the topic, providing background information, stating the problem statement, objectives of the study, limitations, scope, significance, and defining key terms. The literature review explores the current state of NLG technology, its applications in content creation, challenges, ethics, and future trends.

The research methodology chapter outlines the design of the study, data collection methods, NLG model selection, training, and evaluation strategies. The discussion of findings chapter presents the results of the study, including performance evaluation, comparison of NLG models, impact on content creation, user perspectives, ethical considerations, recommendations, and limitations. The thesis concludes with a summary of findings, contributions to the field, implications for practice, future research directions, and a concluding statement on the significance of NLG for automated content creation.

Overall, this thesis aims to contribute to the understanding of how NLG can be effectively utilized for automated content creation and provide insights into the potential benefits and challenges of deploying NLG systems in real-world applications.

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