An Analogous Review of the Challenges and Endeavor in Suspense Story Generation Technique
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-16178-0_9
Reference30 articles.
1. Delatorre, P., León, C., Salguero, A. G., & Tapscott, A. (2020). Predicting the effects of suspenseful outcomes for automatic storytelling. Knowledge-Based Systems, 209, 106450.
2. Delatorre, P., Leon, C., & Hidalgo, A. S. (2021). Improving the Fitness Function of an Evolutionary Suspense Generator Through Sentiment Analysis. IEEE Access, 9, 39626–39635.
3. Das, A., & Verma, R. M. (2020). Can machines tell stories? A comparative study of deep neural language models and metrics. IEEE Access, 8, 181258–181292.
4. Shi, D., Xu, X., Sun, F., Shi, Y., & Cao, N. (2020). Calliope: Automatic visual data story generation from a spreadsheet. IEEE Transactions on Visualization and Computer Graphics, 27(2), 453–463.
5. Lugmayr, A., Sutinen, E., Suhonen, J., Sedano, C. I., Hlavacs, H., & Montero, C. S. (2017). Serious storytelling–a first definition and review. Multimedia tools and applications, 76(14), 15707–15733.
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