time as the most effective fraud detection method in 2011. Out of the available data mining techniques, clustering has … proven itself a constant applied solution for detecting fraud. This paper surveys clustering techniques used in fraud …

Clustering is the process of analyzing data to find clusters of data objects that are similar in some sense to one … another. Some research studies have also extended the usage of clustering concept in inventory management. Yet, not many … research studies have considered the application of clustering approach on determining both optimal order quantity and loss …

data analysis and predictive modeling of information systems. Firstly, they apply clustering to study the information …

apply clustering techniques to data collected in real-time about readmitted patients in Intensive Care Units in order to …

, this article presents an informed sampling method that is based on a clustering approach for the prediction of seismic …

clustering approach. During the investigation, the authors observed that the k-anonymization based clustering approaches all the … generates an optimal cluster with lesser information loss as compared with the existing clustering approaches. …

small number of replications per variable, and HDLLSS data refer to HDLSS data observed over time. Clustering technique …, mass spectrometry data, pattern recognition. Most current clustering algorithms for HDLSS and HDLLSS data are adaptations … addition, available algorithms often exhibit poor clustering accuracy and stability for non-normal data. Simulations show that …