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16th International Conference on Artificial Reality and Telexistence--Workshops (ICAT'06)
Mining Consumers' Most Adaptive Products by Efficient Clustering Algorithm
Hangzhou, China
November 29-December 01
ISBN: 0-7695-2754-X
ASCII Text
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Qingzhang Chen, Jianghong Han, Yuqing Chu, Xiaodong Ying, "Mining Consumers' Most Adaptive Products by Efficient Clustering Algorithm," International Conference on Artificial Reality and Telexistence, pp. 195-199, 16th International Conference on Artificial Reality and Telexistence--Workshops (ICAT'06), 2006.
 
 
BibTex
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@article{ 10.1109/ICAT.2006.84,
author = {Qingzhang Chen and Jianghong Han and Yuqing Chu and Xiaodong Ying},
title = {Mining Consumers' Most Adaptive Products by Efficient Clustering Algorithm},
journal ={International Conference on Artificial Reality and Telexistence},
volume = {0},
year = {2006},
isbn = {0-7695-2754-X},
pages = {195-199},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICAT.2006.84},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - International Conference on Artificial Reality and Telexistence
TI - Mining Consumers' Most Adaptive Products by Efficient Clustering Algorithm
SN - 0-7695-2754-X
SP195
EP199
A1 - Qingzhang Chen,
A1 - Jianghong Han,
A1 - Yuqing Chu,
A1 - Xiaodong Ying,
PY - 2006
KW - null
VL - 0
JA - International Conference on Artificial Reality and Telexistence
ER -
 
Qingzhang Chen, Hefei University of Technology, China; Zhejiang University of Technology, China
Jianghong Han, Hefei University of Technology, China
Yuqing Chu, Zhejiang University of Technology, China
Xiaodong Ying, Zhejiang University of Technology, China
Use clustering methods to discover the individual consumer?s most adaptive products, which can support to make better decisions of marketing service. First, oriented from the consumer?s transactional data that we will mine and targeted by finding some consumer?s most adaptive products, we present a simple and efficient cluster algorithm to put the most similar data into the same group. Then we can find the mined consumer?s most adaptive products from the cluster. Moreover, we propose a Boolean algorithm to improve the performance of the previous.
Citation:
Qingzhang Chen, Jianghong Han, Yuqing Chu, Xiaodong Ying, "Mining Consumers' Most Adaptive Products by Efficient Clustering Algorithm," icat, pp.195-199, 16th International Conference on Artificial Reality and Telexistence--Workshops (ICAT'06), 2006
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