%0 Journal Article
	%A Samira Malekmohammadi Golsefid and  Mehdi Ghazanfari and  Somayeh Alizadeh
	%D 2007
	%J International Journal of Industrial and Manufacturing Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 4, 2007
	%T Customer Segmentation in Foreign Trade based on Clustering Algorithms Case Study: Trade Promotion Organization of Iran
	%U https://publications.waset.org/pdf/10285
	%V 4
	%X The goal of this paper is to segment the countries
based on the value of export from Iran during 14 years ending at 2005. To measure the dissimilarity among export baskets of different countries, we define Dissimilarity Export Basket (DEB) function and
use this distance function in K-means algorithm. The DEB function
is defined based on the concepts of the association rules and the
value of export group-commodities. In this paper, clustering quality
function and clusters intraclass inertia are defined to, respectively,
calculate the optimum number of clusters and to compare the
functionality of DEB versus Euclidean distance. We have also study
the effects of importance weight in DEB function to improve
clustering quality. Lastly when segmentation is completed, a
designated RFM model is used to analyze the relative profitability of
each cluster.
	%P 209 - 215