Natural Language Generation (NLG) techniques have become increasingly important in the field of automated content creation, as they allow for the efficient production of textual data without the need for human intervention. This abstract introduces the various NLG methods and their applications in generating diverse forms of content, such as news articles, product descriptions, and even creative stories. The paper explores the evolution of NLG from rule-based systems to the current state, where deep learning algorithms dominate. It discusses the challenges faced in the development of NLG systems, including maintaining coherence, context understanding, and the generation of high-quality, human-like text. Furthermore, it examines the role of NLG in content personalization and its potential impact on industries such as marketing, education, and customer service. The paper concludes by highlighting future research directions and the importance of ethical considerations in the deployment of NLG technologies.
Jackson, O. Natural Language Generation Techniques for Automated Content Creation. Information Sciences and Technological Innovations, 2022, 4, 36. https://doi.org/10.69610/j.isti.20221221
AMA Style
Jackson O. Natural Language Generation Techniques for Automated Content Creation. Information Sciences and Technological Innovations; 2022, 4(2):36. https://doi.org/10.69610/j.isti.20221221
Chicago/Turabian Style
Jackson, Olivia 2022. "Natural Language Generation Techniques for Automated Content Creation" Information Sciences and Technological Innovations 4, no.2:36. https://doi.org/10.69610/j.isti.20221221
APA style
Jackson, O. (2022). Natural Language Generation Techniques for Automated Content Creation. Information Sciences and Technological Innovations, 4(2), 36. https://doi.org/10.69610/j.isti.20221221
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