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Kasdagli, A. (2019). Medieval history and marxism in England, 1950–1956. Past & Present, 242(1), e1-e43.Search in Google Scholar
Veneziani, R. (2012). Analytical marxism. Journal of Economic Surveys, 26(4), 649-673.Search in Google Scholar
Rasulov, A. (2014). CLS and Marxism: A History of an Affair. Transnational Legal Theory, 5(4), 622-639.Search in Google Scholar
Liu, Y. (2022).Adapting Marxism to outstanding traditional Chinese culture: History, consensus and future. Educational Philosophy and Theory, 1-9.Search in Google Scholar
Bartlová, M. (2012). Czech art history and Marxism. Journal of Art Historiography, 7, 1.Search in Google Scholar
Jerrin, N. B., Bhuvaneswari, G. (2021). Digital Divide: Alarming Agenda of Marxism on the Digital Education Sector. International Journal of Asian Education, 2(3), 327-332.Search in Google Scholar
Wang, Y. (2015). We-media and the popularization of marxism in China. In Proceedings of the International Conference On Creative Education (pp. 175-179).Search in Google Scholar
Ghahramani, Z. (2015). Probabilistic machine learning and artificial intelligence. Nature, 521(7553), 452-459.Search in Google Scholar
Ting, D. S. W., Pasquale, L. R., Peng, L., et al. (2019). Artificial intelligence and deep learning in ophthalmology. British Journal of Ophthalmology, 103(2), 167-175.Search in Google Scholar
Helm, J. M., Swiergosz, A. M., Haeberle, H. S., et al. (2020). Machine learning and artificial intelligence: definitions, applications, and future directions. Current reviews in musculoskeletal medicine, 13(1), 69-76.Search in Google Scholar
Mohassel, P., Rosulek, M., Trieu, N. (2019). Practical privacy-preserving k-means clustering. Cryptology ePrint Archive.Search in Google Scholar
Singh, A., Yadav, A., Rana, A. (2013). K-means with Three different Distance Metrics. International Journal of Computer Applications, 67(10).Search in Google Scholar
Jothi, R., Mohanty, S. K., Ojha, A. (2019). DK-means: a deterministic k-means clustering algorithm for gene expression analysis. Pattern Analysis and Applications, 22(2), 649-667.Search in Google Scholar
Crowston, K., Allen, E. E., Heckman, R. (2012). Using natural language processing technology for qualitative data analysis. International Journal of Social Research Methodology, 15(6), 523-543.Search in Google Scholar
Joseph, S. R., Hlomani, H., Letsholo, K., et al. (2016). Natural language processing: A review. International Journal of Research in Engineering and Applied Sciences, 6(3): 207-210.Search in Google Scholar
Jiao, Y., Qu, Q. X. (2019). A proposal for Kansei knowledge extraction method based on natural language processing technology and online product reviews. Computers in Industry, 108: 1-11.Search in Google Scholar
Zhang, L. (2016). Study on the Application of Web Information Retrieval in the Teaching of Language Translation. International Journal of Emerging Technologies in Learning, 11(4).Search in Google Scholar
Arriany, A. A., Musbah, M. S. (2016). Applying voice recognition technology for smart home networks. 2016 International Conference on Engineering & MIS (ICEMIS). IEEE, 1-6.Search in Google Scholar
Parker, D., Picone, J., Harati, A., et al. (2013). Detecting paroxysmal coughing from pertussis cases using voice recognition technology. PloS one, 8(12), e82971.Search in Google Scholar
Saravanan, D., Srinivasan, S. (2012). Video image retrieval using data mining Techniques. Journal of computer applications (JCA), 5(01), 39-42.Search in Google Scholar
Zhuo, W., He, Z., Zheng, M., et al. (2021). Research on personalized image retrieval technology of video stream big data management model. Multimedia Tools and Applications, 1-18.Search in Google Scholar
Sinaga, K. P., Yang, M. S. (2020). Unsupervised K-means clustering algorithm. IEEE access, 8: 80716-80727.Search in Google Scholar
Mohamad, I. B., Usman, D. (2013). Standardization and its effects on K-means clustering algorithm. Research Journal of Applied Sciences, Engineering and Technology, 6(17), 3299-3303.Search in Google Scholar
Zeebaree, D. Q., Haron, H., Abdulazeez, A. M., et al. (2017). Combination of K-means clustering with Genetic Algorithm: A review. International Journal of Applied Engineering Research, 12(24): 14238-14245.Search in Google Scholar
Wang, X., Xu, Y. (2019). An improved index for clustering validation based on Silhouette index and Calinski-Harabasz index. IOP Conference Series: Materials Science and Engineering. IOP Publishing, 569(5), 052024.Search in Google Scholar
Zhou, H. B., Gao, J. T. (2014). Automatic method for determining cluster number based on silhouette coefficient. Advanced materials research. Trans Tech Publications Ltd, 951, 227-230.Search in Google Scholar
Dinh, D. T., Fujinami, T., Huynh, V. N. (2019). Estimating the optimal number of clusters in categorical data clustering by silhouette coefficient. International Symposium on Knowledge and Systems Sciences. Springer, Singapore, 1-17.Search in Google Scholar