The DOI matches its Crossref record; 51 of the 52 references it cites were found in a registry or an index.
Data mining for credit card fraud: A comparative study
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“This methodology was first proposed by Whitrow et al. (2009) and has been used by a number of studies (Bhattacharyya et al., 2011; Jha et al., 2012; Dal Pozzolo et al., 2014; Bahnsen et al., 2016).”
From Data engineering for fraud detection (2021) · cites this paper as Bhattacharyya et al., 2011
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1 of the 52 references couldn’t be matched to a known paper.
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- Provost, 2002, Comment on Bolton and Hand, Statistical Science, 17, 249
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Explaining prediction models and individual predictions with feature contributions
Štrumbelj, E., & Kononenko, I. (2014) · Knowledge and Information Systems · doi:10.1007/s10115-013-0679-x · Cited by 2,286
“Applications range from credit scoring [11] and fraud detection [5] to financial auditing [4] and efficiency analysis [18].”
BackgroundA comprehensive survey on support vector machine classification: Applications, challenges and trends
Cervantes, J., Garcia-Lamont, F., Rodríguez-Mazahua, L., & Lopez, A. (2020) · Neurocomputing · doi:10.1016/j.neucom.2019.10.118 · Cited by 2,381
A Unifying Review of Deep and Shallow Anomaly Detection
Ruff, L., Kauffmann, J., Vandermeulen, R. A., Montavon, G., Samek, W., Kloft, M., Dietterich, T. G., & Muller, K.-R. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2021.3052449 · Cited by 1,184
A survey of multiple classifier systems as hybrid systems
Woźniak, M., Graña, M., & Corchado, E. (2013) · Information Fusion · doi:10.1016/j.inffus.2013.04.006 · Cited by 930
“Comparing RF against SVM and logisti regression [190], RF was the best performer in all experimental conditions as measured by almost all performance measurements.”
BackgroundMethodFraud detection system: A survey
Abdallah, A., Maarof, M. A., & Zainal, A. B. (2016) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2016.04.007 · Cited by 840
Metadata
- Authors
- Bhattacharyya, S., Jha, S., Tharakunnel, K., & Westland, J. C.
- Affiliations
- University of Illinois Chicago (US)
- University of New Hampshire (US)
- Millikin University (US)
- Corresponding author
- Bhattacharyya, Siddhartha
- Venue
- Decision Support Systems
- Publisher
- Elsevier BV
- Published
- 2011-02
- Volume
- 50
- Issue
- 3
- Pages
- 602-613
- ISSN
- 0167-9236 (ISSN-L)
- OpenAlex
- W2045049630
- Cited by
- 1,108
- References
- 52
- Citations by year
- 2026: 153 · 2025: 142 · 2024: 103 · 2023: 86 · 2022: 98 · 2021: 89 · 2020: 95 · 2019: 83 · 2018: 77 · 2017: 42 · 2016: 34 · 2015: 40 · 2014: 29 · 2013: 17 · 2012: 13
- FWCI
- 11.76
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Decision Support Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Imbalanced Data Classification Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Social Sciences › Business, Management and Accounting › Accounting › Financial Distress and Bankruptcy Prediction
- Keywords
- credit card fraud detection, support vector machine, random forest, logistic regression, transaction data
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