%0 Journal Article
	%A In-Chul Jung and  Young S. Kwon
	%D 2011
	%J International Journal of Economics and Management Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 59, 2011
	%T Grocery Customer Behavior Analysis using RFID-based Shopping Paths Data
	%U https://publications.waset.org/pdf/13460
	%V 59
	%X Knowing about the customer behavior in a grocery has
been a long-standing issue in the retailing industry. The advent of
RFID has made it easier to collect moving data for an individual
shopper's behavior. Most of the previous studies used the traditional
statistical clustering technique to find the major characteristics of
customer behavior, especially shopping path. However, in using the
clustering technique, due to various spatial constraints in the store,
standard clustering methods are not feasible because moving data such
as the shopping path should be adjusted in advance of the analysis,
which is time-consuming and causes data distortion. To alleviate this
problem, we propose a new approach to spatial pattern clustering
based on the longest common subsequence. Experimental results using
real data obtained from a grocery confirm the good performance of the
proposed method in finding the hot spot, dead spot and major path
patterns of customer movements.
	%P 1508 - 1512