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Rudolf: Interactive Rule Refinement System for Fraud Detection

Summary: RUDOLF is an interactive rule-refinement system for fraud detection, enabling experts to adapt rules as fraud and legitimate patterns evolve. It proposes best-rule adaptations to cover frauds and exclude legitimate activity, demonstrated on credit-card and network data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11258
Venue
VLDB
Year
2016
Pagerank
6.6346244e-05
Overall Rank
3,913 | 72.78%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
7,766 ICARUS: Minimizing Human Effort in Iterative Data Completion 2018 VLDB 4.6564959e-05
11,266 MINT: Detecting Fraudulent Behaviors from Time-series Relational Data 2023 VLDB 4.1945683e-05
11,293 Fanglue: An Interactive System for Decision Rule Crafting 2023 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
487 Why Not? 2009 SIGMOD 0.00022050218
3,197 A Probabilistic Optimization Framework for the Empty-Answer Problem 2013 VLDB 7.3955829e-05
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