抽象的な

CLUSTER DETECTION USING GA-KNN CONJUNCTION APPROACH

This Paper provides insights into data mining solution for mining customer�??s information from customer opt-in database of mCRM. The basis of approach is to use a K nearest neighbor algorithm to learn how to classify samples within different clusters of interest. Therefore a new approach using Genetic Algorithm is followed in this paper to overcome some of the shortcomings of the K nearest neighbor algorithm, by allowing the system to learn to warp the n-dimensional feature space so as to maximize the clustering of individuals within a class, and at the same time maximize the separation between classes. The Output of the Genetic Algorithm is acting as input to the K nearest neighbor algorithm And finally the global clusters are being formed and the customization for a particular Customer is done seeing in which Cluster a particular customer falls. The main result of this paper indicates that GA-KNN Conjunction may be an effective element to mCRM. Data mining from the customers�?? database, stores can offer their customers interesting services via the mobile medium (SMS/MMS) and can retain customers with different ways and maintain fruitful relations with their customers based on trust.