OutRules: A Framework for Outlier Descriptions in Multiple Context Spaces
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Cites
Chandola, V., Banerjee, A., & Kumar, V. (2009) · ACM Computing Surveys · doi:10.1145/1541880.1541882 · Cited by 11,687 · see citing works
LOF: identifying density-based local outliers
Breunig, M. M., Kriegel, H.-P., Ng, R. T., & Sander, J. (2000) · ACM SIGMOD Record · doi:10.1145/335191.335388 · Cited by 5,207 · see citing works
Outlier detection for high dimensional data
Aggarwal, C. C., & Yu, P. S. (2001) · ACM SIGMOD International Conference on Management of Data (SIGMOD) · doi:10.1145/375663.375668 · Cited by 1,066 · see citing works
Evaluation Measures for Multi-class Subgroup Discovery
Abudawood, T., & Flach, P. A. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04180-8_20 · Cited by 787 · see citing works
Outlier detection for high dimensional data
Aggarwal, C. C., & Yu, P. S. (2001) · ACM SIGMOD Record · doi:10.1145/376284.375668 · Cited by 443 · see citing works
Finding Intensional Knowledge of Distance-Based Outliers
Knorr, E. M., & Ng, R. T. (1999) · Cited by 419 · see citing works
HiCS: High Contrast Subspaces for Density-Based Outlier Ranking
Keller, F., Müller, E., & Böhm, K. (2012) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde.2012.88 · Cited by 383 · see citing works
Self-citationOutlier Detection in Axis-Parallel Subspaces of High Dimensional Data
Kriegel, H., Kröger, P., Schubert, E., & Zimek, A. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-01307-2_86 · Cited by 324 · see citing works
The design of a query monitoring system
Mishra, C., & Koudas, N. (2009) · ACM Transactions on Database Systems · doi:10.1145/1508857.1508858 · Cited by 169 · see citing works
Statistical selection of relevant subspace projections for outlier ranking
Muller, E., Schiffer, M., & Seidl, T. (2011) · 2011 IEEE 27th International Conference on Data Engineering · doi:10.1109/icde.2011.5767916 · Cited by 126 · see citing works
Self-citationDetecting outlying properties of exceptional objects
Angiulli, F., Fassetti, F., & Palopoli, L. (2009) · ACM Transactions on Database Systems · doi:10.1145/1508857.1508864 · Cited by 88 · see citing works
The Odd One Out: Identifying and Characterising Anomalies
Smets, K., & Vreeken, J. (2011) · SIAM International Conference on Data Mining · doi:10.1137/1.9781611972818.69 · Cited by 69 · see citing works
SOREX: Subspace Outlier Ranking Exploration Toolkit
Müller, E., Schiffer, M., Gerwert, P., Hannen, M., Jansen, T., & Seidl, T. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15939-8_44 · Cited by 14 · see citing works
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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
“Specifically, OutRules explains an anomaly by generating rules that describe the deviation of this instance in contrast to its context.”
BackgroundMethodInfluentialMining outlying aspects on numeric data
Duan, L., Tang, G., Pei, J., Bailey, J., Campbell, A., & Tang, C. (2015) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-014-0398-2 · Cited by 70 · see citing works
Dimension-based subspace search for outlier detection
Trittenbach, H., & Böhm, K. (2018) · International Journal of Data Science and Analytics · doi:10.1007/s41060-018-0137-7 · Cited by 20 · see citing works
Self-citationLP-Explain: Local Pictorial Explanation for Outliers
Liu, H., Ma, F., Wang, Y., He, S., Chen, J., & Gao, J. (2020) · Proceedings · doi:10.1109/icdm50108.2020.00046 · Cited by 8 · see citing works
On the Efficient Explanation of Outlier Detection Ensembles Through Shapley Values
Klüttermann, S., Balestra, C., & Müller, E. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-2259-4_4 · Cited by 5 · see citing works
Self-citationClass-Based Outlier Detection: Staying Zombies or Awaiting for Resurrection?
Nezvalová, L., Popeĺınský, L., Torgo, L., & Vaculík, K. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24465-5_17 · Cited by 4 · see citing works
Information-Theoretic Non-redundant Subspace Clustering
Hubig, N., & Plant, C. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-57454-7_16 · Cited by 3 · see citing works
- Authors
- Müller, E., Keller, F., Blanc, S., & Böhm, K.
- Affiliations
- Karlsruhe Institute of Technology (DE)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2012
- Pages
- 828-832
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W140559943
- Cited by
- 7
- References
- 13
- Citations by year
- 2024: 1 · 2023: 1 · 2020: 1 · 2018: 1 · 2017: 1 · 2015: 2
- FWCI
- 0.49
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Lecture notes in computer science (publishedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (GRK 1194)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
- Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Keywords
- outlier detection
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