China Classical Poetry Art Song Market Trend Forecast and Big Data Analysis in Music Industry

[1] Cho, D., Lee, S. H., Yoo, Y., & Chu, H. Y. (2019). Television singing competitions create stars? Empirical evidence from the digital music chart in South Korea. Journal of Cultural Economics, 43, 1-20. Search in Google Scholar

[2] Astell, A. W. (2018). The Song of Songs in the Middle Ages. Cornell University Press. Search in Google Scholar

[3] Meier, L. M. (2017). Popular music as promotion: Music and branding in the digital age. John Wiley & Sons. Search in Google Scholar

[4] Mehr, S. A., Singh, M., Knox, D., Ketter, D. M., Pickens-Jones, D., Atwood, S., ... & Glowacki, L. (2019). Universality and diversity in human song. Science, 366(6468), eaax0868. Search in Google Scholar

[5] Kuyucu, M. (2021). Music marketing evolution from traditional to digital marketing. Socrates Journal of Interdisciplinary Social Studies, 9, 14-25. Search in Google Scholar

[6] Scott, D. B. (2017). The singing bourgeois: songs of the Victorian drawing room and parlour. Routledge. Search in Google Scholar

[7] Birrell, A. (2022). Popular songs and ballads of Han China. Routledge. Search in Google Scholar

[8] Hujran, O., Alikaj, A., Durrani, U. K., & Al-Dmour, N. (2020, January). Big data and its effect on the music industry. In Proceedings of the 3rd International Conference on Software Engineering and Information Management (pp. 5-9). Search in Google Scholar

[9] Iliya, D. B. (2020). Music promo and marketing in the digital age. JOTAF, 28. Search in Google Scholar

[10] Handke, C. (2020). Music industry. In Handbook of Cultural Economics, Third Edition (pp. 358-370). Edward Elgar Publishing. Search in Google Scholar

[11] Haynes, J., & Marshall, L. (2018). Reluctant entrepreneurs: musicians and entrepreneurship in the ‘new’music industry. The British Journal of Sociology, 69(2), 459-482. Search in Google Scholar

[12] Lomax, A. (2017). Folk song style and culture. Routledge. Search in Google Scholar

[13] Sujan Ghimire,Ravinesh C. Deo,S. Ali Pourmousavi,David Casillas Pérez & Sancho Salcedo Sanz. (2024). Point-based and probabilistic electricity demand prediction with a Neural Facebook Prophet and Kernel Density Estimation model. Engineering Applications of Artificial Intelligence108702-. Search in Google Scholar

[14] Phu Nguyen Duc,Huu Duy Nguyen,Quoc Huy Nguyen,Tan Phan Van & Ha Pham Thanh. (2024). Application of Long Short-Term Memory (LSTM) Network for seasonal prediction of monthly rainfall across Vietnam. Earth Science Informatics(prepubulish),1-20. Search in Google Scholar

[15] Shabnam Bawa,Prashant Singh Rana & RajKumar Tekchandani. (2024). Migration of containers on the basis of load prediction with dynamic inertia weight based PSO algorithm. Cluster Computing (prepubulish), 1-25. Search in Google Scholar