Subspace Projection-Based Clustering and Temporal ACRs Mining on Map Reduce for Direct Marketing Service

Title
Subspace Projection-Based Clustering and Temporal ACRs Mining on Map Reduce for Direct Marketing Service
Author(s)
신용호이헌규[이헌규]정훈[정훈]최용훈[최용훈]
Keywords
ASSOCIATION RULES
Issue Date
201504
Publisher
ELECTRONICS TELECOMMUNICATIONS RESEARCH INST
Citation
ETRI JOURNAL, v.37, no.2, pp.317 - 327
Abstract
A reliable analysis of consumer preference from a large amount of purchase data acquired in real time and an accurate customer characterization technique are essential for successful direct marketing campaigns. In this study, an optimal segmentation of post office customers in Korea is performed using a subspace projection based clustering method to generate an accurate customer characterization from a high-dimensional census dataset. Moreover, a traditional temporal mining method is extended to an algorithm using the Map Reduce framework for a consumer preference analysis. The experimental results show that it is possible to use parallel mining through a Map Reduce-based algorithm and that the execution time of the algorithm is faster than that of a traditional method.
URI
http://hdl.handle.net/YU.REPOSITORY/32736http://dx.doi.org/10.4218/etrij.15.2314.0068
ISSN
1225-6463
Appears in Collections:
경영대학 > 경영학과 > Articles
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