Mining outlying aspects on numeric data
Integrity signals
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The method in [64] is only applicable to density-based anomaly detection.
“Only applicable to density-based AD”
From A Survey on Explainable Anomaly Detection (2024) · cites this paper as [64]
The method in [64] incorporates prior knowledge.
“Incorporates prior knowledge”
From A Survey on Explainable Anomaly Detection (2024) · cites this paper as [64]
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Deep Learning for Anomaly Detection: A Review
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A Survey on Explainable Anomaly Detection
Li, Z., Zhu, Y., & Van Leeuwen, M. (2024) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3609333 · Cited by 139 · see citing works
“[64] develop a method to find its minimal outlying subspace, i.”
MethodDiscovering outlying aspects in large datasets
Vinh, N. X., Chan, J., Romano, S., Bailey, J., Leckie, C., Ramamohanarao, K., & Pei, J. (2016) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-016-0453-2 · Cited by 83 · see citing works
Self-citationSequential Feature Explanations for Anomaly Detection
Siddiqui, M. A., Fern, A., Dietterich, T. G., & Wong, W.-K. (2019) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/3230666 · Cited by 50 · see citing works
Outlying property detection with numerical attributes
Angiulli, F., Fassetti, F., Manco, G., & Palopoli, L. (2017) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-016-0458-x · Cited by 33 · see citing works
Explainable outlier detection: What, for Whom and Why?
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Toward Explainable Deep Anomaly Detection
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A Framework for Outlier Description Using Constraint Programming
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- Authors
- Duan, L., Tang, G., Pei, J., Bailey, J., Campbell, A., & Tang, C.
- Affiliations
- Sichuan University (CN)
- Simon Fraser University (CA)
- The University of Melbourne (AU)
- Corresponding author
- Duan, Lei
- Venue
- Data Mining and Knowledge Discovery
- Published
- 2015-01-17
- Volume
- 29
- Issue
- 5
- Pages
- 1116-1151
- ISSN
- 1384-5810 (ISSN-L)
- 1573-756X
- OpenAlex
- W1999518899
- Cited by
- 70
- References
- 35
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 3 · 2023: 9 · 2022: 10 · 2021: 13 · 2020: 8 · 2019: 5 · 2018: 8 · 2017: 3 · 2016: 5 · 2015: 1
- FWCI
- 5.56
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Data Mining and Knowledge Discovery (publishedVersion)
- Funders
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
- Physical Sciences › Computer Science › Signal Processing › Data Management and Algorithms
- Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
- Keywords
- numerical data, multidimensional data, probability density, heuristic search, high-dimensional data, density-based outlier detection
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