CFP last date
20 May 2024
Reseach Article

Customer Relationship Management Classification by Hybridizing Genetic Algorithm and Fuzzy K-Nearest Neighbor

by Jashandeep Kaur, Rekha Bhatia
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 147 - Number 13
Year of Publication: 2016
Authors: Jashandeep Kaur, Rekha Bhatia
10.5120/ijca2016911286

Jashandeep Kaur, Rekha Bhatia . Customer Relationship Management Classification by Hybridizing Genetic Algorithm and Fuzzy K-Nearest Neighbor. International Journal of Computer Applications. 147, 13 ( Aug 2016), 13-17. DOI=10.5120/ijca2016911286

@article{ 10.5120/ijca2016911286,
author = { Jashandeep Kaur, Rekha Bhatia },
title = { Customer Relationship Management Classification by Hybridizing Genetic Algorithm and Fuzzy K-Nearest Neighbor },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 147 },
number = { 13 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 13-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume147/number13/25713-2016911286/ },
doi = { 10.5120/ijca2016911286 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:51:50.868069+05:30
%A Jashandeep Kaur
%A Rekha Bhatia
%T Customer Relationship Management Classification by Hybridizing Genetic Algorithm and Fuzzy K-Nearest Neighbor
%J International Journal of Computer Applications
%@ 0975-8887
%V 147
%N 13
%P 13-17
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining is the procedure of extraction of data from different datasets on the premise of various attributes. In the CRM, various relational attributes are accessible in the dataset. Information about relations of the customer with the enterprise is available in the dataset. The dataset must be secured utilizing rules for extraction of information. Basically Churn, appetency, up selling and score are the significant entities which will be considered in the proposed work. To eliminate the problems of CRM database a new hybrid algorithm is introduced which will be the combination of GA and Fuzzy KNN classification.

References
  1. S.Ummugulthum Natchiar “Customer Relationship Management Classification Using Data Mining Techniques”, International Conference on Science, Engineering and Management Research, 2014, pp 223-234.
  2. Nedaabdelhamid, Aladdin Ayesh and FadiThabtah “Emerging trends in associative classification data mining” International journal of electronics and electrical engineering Volume 3, Issue 1, Feb 2015.
  3. Sankaranarayanan, S. “Diabetic Prognosis through Data Mining Methods and Techniques”, International Conf. on Intelligent Computing Applications (ICICA), 2014, pp. 162 – 166.
  4. Wang, Guoyin “Granular computing based data mining in the views of rough set and fuzzy set” IEEE Conf. on Granular Computing, 2008, pp. 67.
  5. 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.
  6. Tzung-Pei Hong “GA-based item partition for data mining” IEEE Conf. on Systems, Man, and Cybernetics (SMC), 2011, pp. 2238 – 2242.
  7. 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.
  8. 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.
  9. Alexander Tuzhilin “Customer relationship management and Web mining: the next frontier”, Springer conf. on CRM & WM, 2012, pp 584-612.
  10. 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.
  11. Farnoosh Khodakarami “Exploring the role of customer relationship management (CRM) systems in customer knowledge creation”, Conf. on CRM, 2014, PP 56-70.
  12. Paresh Tanna “Using Apriori with WEKA for Frequent Pattern Mining”, International Journal of Engineering Trends and Technology (IJETT), 2014, pp. 127-131.
  13. Shrey BavisiȦ “A Comparative Study of Different Data Mining Algorithms”, International Journal of Current Engineering vand Technology, 2015, pp. 3248-3252.
  14. Manjari Anand “Customer Relationship Management using Adaptive Resonance Theory”, International Journal of Computer Applications, 2013, pp. 43-47.
  15. Ms. Saranya, “Decision Support System for CRM in Online Shopping System”, International Journal of Advances in Computer Science and Technology, 3(2), February 2014, 148, 2014, pp. 148-151.
Index Terms

Computer Science
Information Sciences

Keywords

CRM Types of CRM Data Mining Genetic Algorithm Fuzzy KNN.