Association rules applied to credit card fraud detection

Author:

Sánchez D.,Vila M.A.,Cerda L.,Serrano J.M.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference35 articles.

1. Agrawal, R., Imielinski, T., & Swami, A. (1993). Mining association rules between set of items in large databases, In Proceedings of the 1993 ACM SIGMOD conference (pp. 207–216).

2. Au, W. H., & Chan, K. C. C. (1998). An effective algorithm for discovering fuzzy rules in relational databases. In Proceedings of IEEE international conference on fuzzy systems (Vol. 5, pp. 1314–1319).

3. A new framework to assess association rules;Berzal,2001

4. Measuring the accuracy and interest of association rules: A new framework;Berzal;Intelligent Data Analysis,2002

5. Berzal, F., Cubero, J. C., Sánchez, D., Serrano, J. M., & Vila, M. A., (2003). Finding fuzzy approximate dependencies within STULONG data. In Proceedings of the ECML/PKDD 2003, Workshop on Discovery Challenge (pp. 34–46). 22–26 September.

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