A NOVAL APPROACH OF DETECTING FRAUDS IN ECOMMERCE SITES BY HYBRIDIZING KNN AND EUCLIDEAN DISTANCE MECHANISM
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Abstract
Lack of time with community is indulging multiple users to participate in online social media for communication. Users can interact with each other through this piece of technology. Ecommerce websites also become popular since users does not have to visit actual stores. As user’s increases, so do frauds. Detection of frauds is the prime objective of this literature. In order to accomplish this KNN and Euclidean distance mechanism is hybridized. Comparative analysis is present against KNN, Euclidean distance and hybrid approach. Results are expressed in terms of time consumption and number of fault detected.
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