Research Article
Customer Relationship Management using Adaptive Resonance Theory
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 76 - Issue 6 |
| Published: August 2013 |
| Authors: Manjari Anand, Zubair Khan, Ravi S. Shukla |
10.5120/13254-0731
|
Manjari Anand, Zubair Khan, Ravi S. Shukla . Customer Relationship Management using Adaptive Resonance Theory. International Journal of Computer Applications. 76, 6 (August 2013), 43-47. DOI=10.5120/13254-0731
@article{ 10.5120/13254-0731,
author = { Manjari Anand,Zubair Khan,Ravi S. Shukla },
title = { Customer Relationship Management using Adaptive Resonance Theory },
journal = { International Journal of Computer Applications },
year = { 2013 },
volume = { 76 },
number = { 6 },
pages = { 43-47 },
doi = { 10.5120/13254-0731 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2013
%A Manjari Anand
%A Zubair Khan
%A Ravi S. Shukla
%T Customer Relationship Management using Adaptive Resonance Theory%T
%J International Journal of Computer Applications
%V 76
%N 6
%P 43-47
%R 10.5120/13254-0731
%I Foundation of Computer Science (FCS), NY, USA
Abstract
CRM is a kind of implemented model for managing a company's interactions with their customers. CRM involves the customer classification to understand the behavior of the customer. There is a vital role of the data mining techniques for the classification. This paper presents the concept of one of the data mining technique ART for the customer classification for CRM.
References
- Leela Rani Komma Reddy and G Loshma. Classification and Prediction in Customer Relationship Management Using Back Propagation. In International Conference on Computer Science and Information Technology, ISBN : 978-93-81693-86-5, 2012.
- Neural Networks in Computer Intelligence by LiMin Fu.
- Huang, C. -L. , Chen, M. -C. , and Wang, C. -J. , (2007). Credit scoring with a data mining approach based on support vector machines. Expert Systems with Applications, 33,847–856.
- Kuykendall L(1999). "The data-mining toolbox"[J]. Credit-Card Management, 12(6):30-40.
- Ching-Hsue Cheng, You-Shyang Chen. Classifying the segmentation of customer value via RFM model and RS theory. Expert Systems with Applications 36 (2009) 4176–4184.
- P. Isakki alias Devi and S. P. Rajagopalan. Analysis of Customer Behavior using Clustering and Associations Rules. International Journal of Computer Applications (0975 – 8887) Volume 43– No. 23, April 2012.
- Jing Zhou, "System of CRM Performance Evaluation Based on Fuzzy Comprehensive Algorithm", IEEE 2008.
- Huo, Gao ,"Customer relationship management based on data mining technique — Naive Bayesian classifier", IEEE 2011.
- Al-Mudimigh, A. S. ; Ullah, Z. ; Saleem, F. , "Data mining strategies and techniques for CRM systems",IEEE 2009.
- Wei Wang; Shidong Fan, "Application of Data Mining Technique in Customer Segmentation of Shipping Enterprises, IEEE 2010.
- Qiang Yang; Jie Yin; Ling, C. X. ; Chen, "Post-processing decision trees to extract actionable knowledge", IEEE 2003.
- Chris Rygielski, Jyun-Cheng Wang, David C. Yen, "Data mining techniques for customer relationship management", 0160-791X/02/$ - see front matter 2002 Elsevier Science Ltd. All rights reserved. PII: S01 60 -791X(02)00038-6.
- S. Balaji ,"Naïve Bayes Classification Approach for Mining Life Insurance Databases for Effective Prediction of Customer Preferences over Life Insurance Products".
- Introduction to Neural Networks using MATLAB 6. 0 by S. N. Srivanandam, S. Deepa.
Index Terms
Keywords