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Neural Networks in ERP and CRM

by Mary. A. S., P. Ranjit Jeba Thangaiah
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 39 - Number 1
Year of Publication: 2012
Authors: Mary. A. S., P. Ranjit Jeba Thangaiah
10.5120/4781-6980

Mary. A. S., P. Ranjit Jeba Thangaiah . Neural Networks in ERP and CRM. International Journal of Computer Applications. 39, 1 ( February 2012), 1-3. DOI=10.5120/4781-6980

@article{ 10.5120/4781-6980,
author = { Mary. A. S., P. Ranjit Jeba Thangaiah },
title = { Neural Networks in ERP and CRM },
journal = { International Journal of Computer Applications },
issue_date = { February 2012 },
volume = { 39 },
number = { 1 },
month = { February },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-3 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume39/number1/4781-6980/ },
doi = { 10.5120/4781-6980 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:25:16.766476+05:30
%A Mary. A. S.
%A P. Ranjit Jeba Thangaiah
%T Neural Networks in ERP and CRM
%J International Journal of Computer Applications
%@ 0975-8887
%V 39
%N 1
%P 1-3
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Enterprise Resource Planning (ERP) is a very popular term nowadays which integrates all the major functions like Finance, Controlling, Production, Selling and Distribution, Personnel, Quality Control, Material management of the concern. ERP is applicable both in big and medium size industries. CRM mainly concentrates to satisfy the consumers at a maximum level. Data mining is a computer technique which helps to coordinate these two parts through the way of applying best algorithm and deriving the results. This research paper uses neural networks for obtaining customer value as well as product value for a specific customer or product. Then these customer or product values are to be combined into clusters by using K-Mean algorithm. The testing results prove that this method gives more accuracy than Naïve Bayes and Decision tree J-48 classification techniques. Experimental results show a satisfactory performance. The results obtained from this research work helps the organization to find out a most suitable marketing strategy in the near future.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Enterprise Resource Planning Customer relationship management Naïve Bayes Neural networks

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