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Improving telemarketing intelligence through significant proportion of target instances

Tan, Ding-Wen, Liew,Soung-Yue and Yeoh, William 2014, Improving telemarketing intelligence through significant proportion of target instances, in PACIS 2014 : Proceedings of the Pacific Asia Conference on Information Systems 2014, AIS eLiberary, [Chengdu, China], pp. 1-15.

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Title Improving telemarketing intelligence through significant proportion of target instances
Author(s) Tan, Ding-Wen
Liew,Soung-Yue
Yeoh, William
Conference name Pacific Asia Conference on Information Systems (2014 : Chengdu, China)
Conference location Chengdu, China
Conference dates 24-28 Jun. 2014
Title of proceedings PACIS 2014 : Proceedings of the Pacific Asia Conference on Information Systems 2014
Editor(s) Siau, Keng
Li, Qing
Guo, Xunhua
Publication date 2014
Conference series Pacific Asia Conference on Information Systems
Start page 1
End page 15
Total pages 15
Publisher AIS eLiberary
Place of publication [Chengdu, China]
Keyword(s) telemarketing
data mining
feature selection
binary classification
imbalance data
Summary In this paper we propose, develop, and test a new single-feature evaluator called Significant Proportion of Target Instances (SPTI) to handle the direct-marketing data with the class imbalance problem. The SPTI feature evaluator demonstrates its stability and outstanding performance through empirical experiments in which the real- orld customer data of an e-recruitment firm are used. This research demonstrates that the feature selection using SPTI successfully improves the classifier’s performance in terms of two practical performance metrics. Additionally, we show that it outperforms other well-known feature selection methods and state-of-the-art remedies to the class-imbalance problem. Practically, the findings, when used with the classification model, will help telemarketers to better understand their customers.
Language eng
Field of Research 080605
Socio Economic Objective 890299 Computer Software and Services not elsewhere classified
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2014, AIS
Persistent URL http://hdl.handle.net/10536/DRO/DU:30066568

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.