Fraud Pattern Mining
Fraud Pattern Mining is a data analytics methodology that identifies distinctive and statistically significant behavioral patterns indicative of fraudulent activities within transactional or operational datasets by applying computational techniques to distinguish anomalous, fraud-related sequences from legitimate ones.
292
Publications
21.1K
Citations
837
Authors
364
Institutions
Publications per year
2017–2026
151
Parents
292
Data mining for credit card fraud: A comparative study
Siddhartha Bhattacharyya, Sanjeev Jha, Kurian Tharakunnel et al. · Decision Support Systems · 2010 · 963 citations
Business, Computer Science, Finance +16
1–5 of 292
837
5
h-index
5
h-index
4
h-index
4
h-index
4
h-index
1–5 of 837
364
Tongji University
Shanghai, China
8 h-index
29 publications
1.1K citations
Decision Sciences (United States)
Fort Walton Beach, United States
5 h-index
9 publications
3.5K citations

University of Cagliari
Cagliari, Italy
4 h-index
8 publications
232 citations

Charles Sturt University
Bathurst, Australia
3 h-index
5 publications
80 citations
Institut National des Sciences Appliquées de Lyon
Lyon, France
3 h-index
7 publications
1.2K citations
Shandong University of Science and Technology
Qingdao, China
3 h-index
9 publications
495 citations
Rutgers, The State University of New Jersey
New Brunswick, United States
3 h-index
3 publications
134 citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
3 h-index
6 publications
176 citations
1–8 of 364
16 publications · 3.3K citations
16
h-index
8 publications · 3.4K citations
8
h-index
7 publications · 287 citations
7
h-index
5 publications · 164 citations
5
h-index
4 publications · 470 citations
4
h-index
1–5