This work is licensed under the Creative Commons Attribution 4.0 International License.
Creeber, G. (Ed.). (2023). The television genre book. Bloomsbury Publishing.Search in Google Scholar
Spottiswoode, R. (2022). Film and its techniques. Univ of California Press.Search in Google Scholar
Donnelly, K. (2019). The spectre of sound: Music in film and television. Bloomsbury Publishing.Search in Google Scholar
Dolan, J. S. (2017). The Feminist Spectator in Action: Feminist Criticism for the Stage and Screen. Bloomsbury Publishing.Search in Google Scholar
Salihu, A. (2024). THEORY OF RECEPTION AND CRITICISM OF FILMS BASED ON THE RECEPTION AND CRITICISM OF THE FILM “ANNA KARENINA”(1997). FILOLOGJIA International Journal of Human Sciences, 12(22-23), 38-53.Search in Google Scholar
Benson-Allott, C. (2021). The Stuff of Spectatorship: Material Cultures of Film and Television. University of California Press.Search in Google Scholar
Cooper, A. (2019). Neoliberal theory and film studies. New Review of Film and Television Studies, 17(3), 265-277.Search in Google Scholar
Perkins, C., & Schreiber, M. (2019). Independent women: from film to television. Feminist Media Studies, 19(7), 919-927.Search in Google Scholar
Yang, J., Wang, H., Lv, Z., Wei, W., Song, H., Erol-Kantarci, M., ... & He, S. (2017). Multimedia recommendation and transmission system based on cloud platform. Future Generation Computer Systems, 70, 94-103.Search in Google Scholar
Williams, S. (2017). Popular television drama: critical perspectives. Manchester University Press.Search in Google Scholar
Indira, K., & Kavithadevi, M. K. (2019). Efficient machine learning model for movie recommender systems using multi-cloud environment. Mobile Networks and Applications, 24(6), 1872-1882.Search in Google Scholar
Johnson, C. (2017). Beyond catch-up: VoD interfaces, ITV Hub and the repositioning of television online. Critical Studies in Television, 12(2), 121-138.Search in Google Scholar
Liu, X., Singh, P. V., & Srinivasan, K. (2016). A structured analysis of unstructured big data by leveraging cloud computing. Marketing science, 35(3), 363-388.Search in Google Scholar
Kydd, E. (2017). The critical practice of film: an introduction. Bloomsbury Publishing.Search in Google Scholar
Yang, J., & Yecies, B. (2016). Mining Chinese social media UGC: a big-data framework for analyzing Douban movie reviews. Journal of Big Data, 3, 1-23.Search in Google Scholar
Paxton, R. J., & Marcus, A. S. (2018). Film media in history teaching and learning. The Wiley international handbook of history teaching and learning, 579-601.Search in Google Scholar
Awan, M. J., Khan, R. A., Nobanee, H., Yasin, A., Anwar, S. M., Naseem, U., & Singh, V. P. (2021). A recommendation engine for predicting movie ratings using a big data approach. Electronics, 10(10), 1215.Search in Google Scholar
Prammaggiore, M., & Wallis, T. (2020). Film Fourth Edition: A Critical Introduction. Laurence King Publishing.Search in Google Scholar
Koneru, A., Bhavani, N. B. N. S. R., Rao, K. P., Prakash, G. S., Kumar, I. P., & Kumar, V. V. (2018, May). Sentiment analysis on top five cloud service providers in the market. In 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI) (pp. 293-297). IEEE.Search in Google Scholar
Peiyang Wei,Mingsheng Shang,Jiesan Zhou & Xiaoyu Shi. (2024). Efficient adaptive learning rate for convolutional neural network based on quadratic interpolation egret swarm optimization algorithm. Heliyon(18),e37814-e37814.Search in Google Scholar
Jinfu Chen,Haodi Xie,Saihua Cai,Luo Song,Bo Geng & Wuhao Guo. (2024). GCN-MHSA: A novel malicious traffic detection method based on graph convolutional neural network and multi-head self-attention mechanism. Computers & Security104083-104083.Search in Google Scholar
A. Quadir,M.A. Ganaie & M. Tanveer. (2024). Intuitionistic fuzzy generalized eigenvalue proximal support vector machine. Neurocomputing128258-128258.Search in Google Scholar