अमूर्त

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.

अस्वीकृति: इस सारांश का अनुवाद कृत्रिम बुद्धिमत्ता उपकरणों का उपयोग करके किया गया है और इसे अभी तक समीक्षा या सत्यापित नहीं किया गया है।

में अनुक्रमित

Google Scholar
Academic Journals Database
Open J Gate
Academic Keys
ResearchBible
CiteFactor
Electronic Journals Library
RefSeek
Hamdard University
Scholarsteer
International Innovative Journal Impact Factor (IIJIF)
International Institute of Organised Research (I2OR)
Cosmos

और देखें