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Netw."},{"key":"10.1016\/j.jpdc.2020.07.008_b154","article-title":"Elephant flow detection and differentiated scheduling with efficient sampling and classification","author":"Tang","year":"2019","journal-title":"IEEE Trans. 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Commun. Rev."},{"key":"10.1016\/j.jpdc.2020.07.008_b159","series-title":"Proceedings of the Eighth International Symposium on Information and Communication Technology","first-page":"333","article-title":"A deep learning based method for handling imbalanced problem in network traffic classification","author":"Vu","year":"2017"},{"key":"10.1016\/j.jpdc.2020.07.008_b160","first-page":"577","article-title":"Constrained k-means clustering with background knowledge","volume":"vol. 1","author":"Wagstaff","year":"2001"},{"key":"10.1016\/j.jpdc.2020.07.008_b161","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1145\/1064413.1064417","article-title":"A methodology for study persistency aspects of internet flows","volume":"35","author":"Wallerich","year":"2005","journal-title":"ACM SIGCOMM Comput. Commun. 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