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Genetic K-means Algorithm for Credit Card Fraud Detection
| Content Provider | Semantic Scholar |
|---|---|
| Author | Chougule, Pooja Thakare, Anuradha D. Kale, Prajakta Suhasrao Gole, Madhura Nanekar, Priyanka |
| Copyright Year | 2015 |
| Abstract | Rapid growth in electronic commerce technology has led to a tremendous increase in the use of online credit card payment mode. With the usage of credit cards, the number of frauds associated with it also increases. In order to avoid credit card frauds, proper security measures need to be taken. This work reflects an attempt to detect fraudulent credit card transactions by using k-means along with genetic algorithm. Genetic Algorithm is a powerful optimization technique. The k-means algorithm groups the credit card transactions based on the independent attribute values. But, with the increase in input size, it results in outliers. Hence to provide optimized detection of frauds, we used genetic algorithm. The significant results by proposed model are observed over simple K-means and Simple Genetic Algorithm. Keywords— Fraud Detection, E-commerce technology, Credit Card, K-means, Genetic Algorithm (GA), Data Mining. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijcsit.com/docs/Volume%206/vol6issue02/ijcsit20150602177.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
