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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 2, 2013.
Abstract: Customer’s behavior and satisfaction are always play important role to increase organization’s growth and market value. Customers are on top priority for the growing organization to build up their businesses. In this paper presents the architecture of Decision Support Systems (DSS) in connection to deal with the customer’s enquiries and requests. Main purpose behind the proposed model is to enhance the customer’s satisfaction and behavior using DSS. We proposed model by extension in traditional DSS concepts with integration of Data Mining (DM) abstract. The model presented in this paper shows the comprehensive architecture to work on the customer requests using DSS and knowledge management (KM) for improving the customer’s behavior and satisfaction. Furthermore, DM abstract provides more methods and techniques; to understand the contacted customer’s data, to classify the replied answers in number of classes, and to generate association between the same type of queries, and finally to maintain the KM for future correspondence.
Abdullah Saad AL-Malaise, “Integration of Automated Decision Support Systems with Data Mining Abstract: A Client Perspective” International Journal of Advanced Computer Science and Applications(IJACSA), 4(2), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040226
@article{AL-Malaise2013,
title = {Integration of Automated Decision Support Systems with Data Mining Abstract: A Client Perspective},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.040226},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040226},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {2},
author = {Abdullah Saad AL-Malaise}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.