నైరూప్య

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.

నిరాకరణ: ఈ సారాంశం ఆర్టిఫిషియల్ ఇంటెలిజెన్స్ టూల్స్ ఉపయోగించి అనువదించబడింది మరియు ఇంకా సమీక్షించబడలేదు లేదా నిర్ధారించబడలేదు

ఇండెక్స్ చేయబడింది

Google Scholar
Academic Journals Database
Open J Gate
Academic Keys
ResearchBible
CiteFactor
ఎలక్ట్రానిక్ జర్నల్స్ లైబ్రరీ
RefSeek
హమ్దార్డ్ విశ్వవిద్యాలయం
విద్వాంసుడు
ఇంటర్నేషనల్ ఇన్నోవేటివ్ జర్నల్ ఇంపాక్ట్ ఫ్యాక్టర్ (IIJIF)
ఇంటర్నేషనల్ ఇన్స్టిట్యూట్ ఆఫ్ ఆర్గనైజ్డ్ రీసెర్చ్ (I2OR)
కాస్మోస్

మరిన్ని చూడండి