C4.5: programs for machine learning
C4.5: programs for machine learning
Data Mining and Knowledge Discovery
A decision-theoretic generalization of on-line learning and an application to boosting
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Dissecting Computer Fraud: From Definitional Issues to a Taxonomy
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 7 - Volume 7
Minority report in fraud detection: classification of skewed data
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Lazy Associative Classification
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Detecting fraudulent personalities in networks of online auctioneers
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
A traffic shaping optimization methodology for web systems
Proceedings of the 19th Brazilian symposium on Multimedia and the web
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Due to the growing popularity of the Web, there is an increasing number of people who performs e-business transactions. On the other hand, this popularity has also attracted the attention of criminals, raising the number of fraud cases in Web and financial losses that reach billions of dollars per year. This paper proposes a methodology, based on the knowledge discovery process, to detect fraud in online payment systems. In order to evaluate this methodology we define the concept of economical efficiency and applied it to an actual dataset of one of the largest Latin American electronic payment systems. The results show a very good performance for our proposal, providing gains of up to 46.5% in comparison with the strategy currently employed.