Research Article
Customer Relationship Management Classification by Hybridizing Genetic Algorithm and Fuzzy K-Nearest Neighbor - A Review
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 146 - Issue 9 |
| Published: Jul 2016 |
| Authors: Jashandeep Kaur, Rekha Bhatia |
10.5120/ijca2016910890
|
Jashandeep Kaur, Rekha Bhatia . Customer Relationship Management Classification by Hybridizing Genetic Algorithm and Fuzzy K-Nearest Neighbor - A Review. International Journal of Computer Applications. 146, 9 (Jul 2016), 25-27. DOI=10.5120/ijca2016910890
@article{ 10.5120/ijca2016910890,
author = { Jashandeep Kaur,Rekha Bhatia },
title = { Customer Relationship Management Classification by Hybridizing Genetic Algorithm and Fuzzy K-Nearest Neighbor - A Review },
journal = { International Journal of Computer Applications },
year = { 2016 },
volume = { 146 },
number = { 9 },
pages = { 25-27 },
doi = { 10.5120/ijca2016910890 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2016
%A Jashandeep Kaur
%A Rekha Bhatia
%T Customer Relationship Management Classification by Hybridizing Genetic Algorithm and Fuzzy K-Nearest Neighbor - A Review%T
%J International Journal of Computer Applications
%V 146
%N 9
%P 25-27
%R 10.5120/ijca2016910890
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Data mining is the process of extraction of information from various datasets on the basis of different attributes. Mining has to be done to extract hidden relationship between various database entities. In the customer relationship management, a choice of relational attributes are available in the dataset. In this paper various techniques are used for the customer relationship.
References
- S.Ummugulthum Natchiar “Customer Relationship Management Classification Using Data Mining Techniques”, International Conference on Science, Engineering and Management Research, 2014, pp 223-234.
- Nedaabdelhamid, Aladdin Ayesh and FadiThabtah “Emerging trends in associative classification data mining” International journal of electronics and electrical engineering Feb 2015.
- Sankaranarayanan, S. “Diabetic Prognosis through Data Mining Methods and Techniques”, International Conf. on Intelligent Computing Applications (ICICA), 2014, pp. 162 – 166.
- Wang, Guoyin “Granular computing based data mining in the views of rough set and fuzzy set” IEEE Conf. on Granular Computing, 2008, pp. 67.
- Tzung-Pei Hong “Using divide-and-conquer GA strategy in fuzzy data mining” IEEE Conf. on Computers and Communications, 2004, pp. 116 - 121 Vol.1.
- Tzung-Pei Hong “GA-based item partition for data mining” IEEE Conf. on Systems, Man, and Cybernetics (SMC), 2011, pp. 2238 – 2242.
- Jo-Ting Wei “Customer relationship management in the hairdressing industry: An application of data mining techniques”, IEEE Conf. on Expert Systems with Applications, 2013, pp Pages 7513–7518.
- Wen-Yu Chiang “Applying data mining with a new model on customer relationship management systems: a case of airline industry in Taiwan”, Conf. on Data Mining, 2014, pp 89-97.
- Alexander Tuzhilin “Customer relationship management and Web mining: the next frontier”, Springer conf. on CRM & WM, 2012, pp 584-612.
- Siavash Emtiyaz “Customers Behavior Modeling by Semi-Supervised Learning in Customer Relationship Management”, Advances in information Sciences and Service Sciences (AISS), 2011, PP 56-67.
- Shu-Hsien Liao “Data mining techniques and applications – A decade review from 2000 to 2011”, Expert Systems with Applications, 2012, PP 11303–11311.
- Farnoosh Khodakarami “Exploring the role of customer relationship management (CRM) systems in customer knowledge creation”, Conf. on CRM, 2014, PP 56-70.
- Md. Rashid Farooqi “A Comprehensive Study of CRM through Data Mining Techniques” Proceedings of the National Conference; NCCIST-2011,pp.6-11.
Index Terms
Keywords