Anomaly detection methods for categorical data: A review
Author's Department
Mathematics & Actuarial Science Department
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https://doi.org/10.1145/3312739
Document Type
Research Article
Publication Title
ACM Computing Surveys
Publication Date
5-1-2019
doi
10.1145/3312739
Recommended Citation
APA Citation
Taha, A.
&
Hadi, A.
(2019). Anomaly detection methods for categorical data: A review. ACM Computing Surveys, 52(2),
10.1145/3312739
https://fount.aucegypt.edu/faculty_journal_articles/957
MLA Citation
Taha, Ayman, et al.
"Anomaly detection methods for categorical data: A review." ACM Computing Surveys, vol. 52,no. 2, 2019,
https://fount.aucegypt.edu/faculty_journal_articles/957
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