The DOI matches its Crossref record.
Outlier Analysis
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In the past two decades, most research on anomaly detection has focused on improving the accuracy of the detection, while largely ignoring the explainability of the corresponding methods and thus leaving the explanation of outcomes to practitioners.”
From A Survey on Explainable Anomaly Detection (2024) · cites this paper as [1]
In the citing paper
“Since the seminal work in [105], anomaly detection has been well studied and there exists a plethora of comprehensive surveys and reviews on it, including but not limited to References [1,5,25,36,37,134,135,161,165,231].”
From A Survey on Explainable Anomaly Detection (2024) · cites this paper as [1]
Citations
Cites
Still being checked.
Cited by
Sorted by citations
Items 301–304 of 304
Patron insights and product recommendations using machine learning algorithms
Naidu, C. S. K. V. R., Subhash, K., Sudheer, K. T., Sai, G. B. P., & Sagar, M. H. (2026) · AIP conference proceedings · doi:10.1063/5.0341818
Anomaly Assessment of Time Series Data in Real-Time Using Consensus-Based Ensemble Validation
Gupta, R., Srivastava, R. P., & Sharma, S. (2026) · OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry (OTCON) · doi:10.1109/otcon69332.2026.11629853
Predictors of overweight and obesity among urban office workers in the Philippines
Oliveira, M. R. D. J. (2016) · doi:10.63201/nsep8898
Ghulaxe, V. (2025) · Research Journal of Engineering and Technology · doi:10.52711/2321-581x.2025.00011
Metadata
- Authors
- Aggarwal, C. C.
- Venue
- Data Mining
- Publisher
- Springer International Publishing
- Published
- 2015
- Pages
- 237-263
- OpenAlex
- W4239954780
- Cited by
- 305
- References
- 0
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 18 · 2023: 22 · 2022: 33 · 2021: 63 · 2020: 60 · 2019: 34 · 2018: 29 · 2017: 18 · 2016: 12
- FWCI
- 39.18
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Data Classification
- Keywords
- outlier analysis, outliers, anomaly detection
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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