The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
On-line outlier detection and data cleaning
Overview
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Registry
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Claims the paper makes
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Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
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Citations
Cites
Huber, P. J. (1981) · Wiley Series in Probability and Statistics · doi:10.1002/0471725250 · Cited by 7,066
Robust Regression and Outlier Detection
Rousseeuw, P. J., & Leroy, A. M. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/0471725382 · Cited by 5,609
Least Median of Squares Regression
Rousseeuw, P. J. (1984) · Journal of the American Statistical Association · doi:10.1080/01621459.1984.10477105 · Cited by 3,835
A Fast Algorithm for the Minimum Covariance Determinant Estimator
Rousseeuw, P. J., & Driessen, K. V. (1999) · Technometrics · doi:10.1080/00401706.1999.10485670 · Cited by 2,708
The Influence Curve and its Role in Robust Estimation
Hampel, F. R. (1974) · Journal of the American Statistical Association · doi:10.1080/01621459.1974.10482962 · Cited by 2,706
A General Qualitative Definition of Robustness
Hampel, F. R. (1971) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177693054 · Cited by 1,002
Robust $M$-Estimators of Multivariate Location and Scatter
Maronna, R. A. (1976) · The Annals of Statistics · doi:10.1214/aos/1176343347 · Cited by 952
Fox, A. J. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00912.x · Cited by 756
Outliers, level shifts, and variance changes in time series
Tsay, R. S. (1988) · Journal of Forecasting · doi:10.1002/for.3980070102 · Cited by 722
The identification of multiple outliers
Davies, L., & Gather, U. (1993) · Journal of the American Statistical Association · doi:10.1080/01621459.1993.10476339 · Cited by 709
Cited by
Data Mining and Analytics in the Process Industry: The Role of Machine Learning
Ge, Z., Song, Z., Ding, S. X., & Huang, B. (2017) · IEEE Access · doi:10.1109/access.2017.2756872 · Cited by 922
“be removed from the modeling dataset, which will otherwise greatly deteriorate the performance of the machine learning model [19].”
BackgroundGeneralized Out-of-Distribution Detection: A Survey
Yang, J., Zhou, K., Li, Y., & Liu, Z. (2024) · International Journal of Computer Vision · doi:10.1007/s11263-024-02117-4 · Cited by 884
A comparative evaluation of outlier detection algorithms: Experiments and analyses
Domingues, R., Filippone, M., Michiardi, P., & Zouaoui, J. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2017.09.037 · Cited by 452
Scardulla, F., D’Acquisto, L., Colombarini, R., Hu, S., Pasta, S., & Bellavia, D. (2020) · Sensors · doi:10.3390/s20185052 · Cited by 72
A three level hierarchical architecture for an efficient storage of Industry 4.0 data
Villalobos, K., Ramírez-Durán, V. J., Diez, B., Blanco, J. M., Goñi, A., & Illarramendi, A. (2020) · Computers in Industry · doi:10.1016/j.compind.2020.103257 · Cited by 35
Metadata
- Authors
- LIU, H.
- Venue
- Computers & Chemical Engineering
- Publisher
- Elsevier BV
- Published
- 2004-08
- Volume
- 28
- Issue
- 9
- Pages
- 1635-1647
- ISSN
- 0098-1354 (ISSN-L)
- OpenAlex
- W4234967753
- Cited by
- 256
- References
- 18
- FWCI
- 6.42
- Type
- journal article
- Language
- en
- Open access
- closed
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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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: On-line outlier detection and data cleaning. https://app.cochat.ai/papers/10.1016/s0098-1354(04)00024-9
- The paper
- LIU, H. (2004). On-line outlier detection and data cleaning. Computers & Chemical Engineering. https://doi.org/10.1016/s0098-1354(04)00024-9
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
