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English Information

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Authors
# Name
1 Rodrigo Silva(rsilva.1998@alunos.utfpr.edu.br)
2 Luiz Gomes(gomesjr@dainf.ct.utfpr.edu.br)

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Reference
# Reference
1 Chandola, V., Banerjee, A., and Kumar, V. (2009). Anomaly detection: A survey. ACM Computing Surveys, 41(3):15:1–15:58
2 Cheng, Z., Zou, C., and Dong, J. (2019). Outlier detection using isolation forest and local outlier factor. In Proceedings of the Conference on Research in Adaptive and Convergent Systems, RACS ’19, pages 161–168, New York, NY, USA. Association for Computing Machinery
3 Samariya, D., Aryal, S., and Ting, K. M. (2020a). A new effective and efficient measure for outlying aspect mining. arXiv: 2004.13550
4 Samariya, D., Ma, J., and Aryal, S. (2020b). A Comprehensive Survey on Outlying Aspect Mining Methods. arXiv: 2005.02637
5 the Vinh, N., Chan, J., Romano, S., Bailey, J., Leckie, C., Ramamohanarao, K., and Pei, J. (2016). Discovering outlying aspects in large datasets. Data Mining and Knowledge Discovery, 30