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2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04)
Personalized Product Recommendation in e-Commerce
Taipei, Taiwan
March 28-March 31
ISBN: 0-7695-2073-1
ASCII Text
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Sung-Shun Weng, Mei-Ju Liu, "Personalized Product Recommendation in e-Commerce," e-Technology, e-Commerce, and e-Services, IEEE International Conference on, pp. 413-420, 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04), 2004.
 
 
BibTex
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@article{ 10.1109/EEE.2004.1287340,
author = {Sung-Shun Weng and Mei-Ju Liu},
title = {Personalized Product Recommendation in e-Commerce},
journal ={e-Technology, e-Commerce, and e-Services, IEEE International Conference on},
volume = {0},
year = {2004},
isbn = {0-7695-2073-1},
pages = {413-420},
doi = {http://doi.ieeecomputersociety.org/10.1109/EEE.2004.1287340},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - e-Technology, e-Commerce, and e-Services, IEEE International Conference on
TI - Personalized Product Recommendation in e-Commerce
SN - 0-7695-2073-1
SP413
EP420
A1 - Sung-Shun Weng,
A1 - Mei-Ju Liu,
PY - 2004
KW - null
VL - 0
JA - e-Technology, e-Commerce, and e-Services, IEEE International Conference on
ER -
 
Sung-Shun Weng, Fu Jen University
Mei-Ju Liu, Fu Jen University
The purpose of this paper is to analyze customers? purchasing behaviors based on product features from transaction records and product feature databases. Customers? preferences toward particular features of products are analyzed and then rules of customer interest profiles are thus derived in order to recommend customers products that have potential attraction with customers. The approach of this paper has its strength to be able to recommend to customers brand new products or rarely purchased products as long as they fit customer interest profiles. This research also derives customers? interest profiles that can explain recommendation results. The interests on particular features of products can be referenced for product development.
Citation:
Sung-Shun Weng, Mei-Ju Liu, "Personalized Product Recommendation in e-Commerce," eee, pp.413-420, 2004 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'04), 2004
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