CFP last date
20 January 2025
Reseach Article

Data Mining in E-Commerce: A CRM Platform

by Lipsa Sadath
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 68 - Number 24
Year of Publication: 2013
Authors: Lipsa Sadath
10.5120/11729-7383

Lipsa Sadath . Data Mining in E-Commerce: A CRM Platform. International Journal of Computer Applications. 68, 24 ( April 2013), 32-37. DOI=10.5120/11729-7383

@article{ 10.5120/11729-7383,
author = { Lipsa Sadath },
title = { Data Mining in E-Commerce: A CRM Platform },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 68 },
number = { 24 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 32-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume68/number24/11729-7383/ },
doi = { 10.5120/11729-7383 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:28:48.977277+05:30
%A Lipsa Sadath
%T Data Mining in E-Commerce: A CRM Platform
%J International Journal of Computer Applications
%@ 0975-8887
%V 68
%N 24
%P 32-37
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data is considered as a basic form of information that needs collection, management, mining and interpretation to create knowledge. Modern e-commerce is also vigorously developing that makes resources and services on the internet richly colorful. At the same time there are lots of fraudulent situations happening with people coming closer to the e-commerce system. This is an era where e-commerce is considered to be a killer-domain for successful mining data as it gives the apt ingredients from situation to situation. One of oldest things that e-commerce can do is customer relationship management (CRM). Businesses targeting customers has a direct link with the economy of a country as the current e-commerce system is used by people from lay man to business tycoons. The paper aims at a study on e-commerce with data mining proposing architectural model integrating an improved CRM system for handling business predictions and make strategies to enhance best customer relationship management.

References
  1. Gini Rometty, CEO, IBM, New York, Speech, Council on Foreign Relations in New York,Newspaper, Times of Oman, March 11, 2013.
  2. Berry, M. J. A. , & Linnof, G, Data mining Techniques, New York: Wiley, (1997).
  3. Agrawal, R. , Imielinski, T. , and Swami, A. , 1993. Mining association rules between sets of items in large databases. In Proceedings of the ACM SIGMOD International Conference on Management of Data (ACM SIGMOD '93), pages 207 – 216, Washington, USA
  4. Agrawal, R. and Srikant, R. , 1994. "Fast algorithms for mining association rules" in Proceedings of the 20th International Conference on Very Large Databases (VLDB '94), Santiago, Chile
  5. Agrawal, R. and Shim, K. , 1996. Developing tightlycoupled data mining applications on a relational database system in Proceedings of the 2nd International Conference on Knowledge Discovery in Databases and Data Mining (KDD '96), Portland, Oregon, USA
  6. Data mining definition available at http://www. gartner. com/it-glossary/data-mining
  7. Ansari, S. , Kohavi,R. , Mason, L. , and Zheng, Z. , 2001. Integrating E-Commerce and Data Mining, Blue Martini Software Technical, Report, 2001, Available from the articles section of http://developer. bluemartini. com
  8. Kohavi, R. , 2001. Mining e-commerce data: The good, the bad, and the ugly (invited industrial track talk). In Foster Provost and Ramakrishnan Srikant, editors, Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2001. http://robotics. Stanford. EDU/users/ronnyk/goodBadUglyKDDItrack. pdf
  9. Mehmed M. Kantardzic, Jozef Zurada, Next Generation of Data Mining Apllications,Wiley Interscience,IEEE,ISBN 0-471-65605-4
  10. Cooley, R. , Mobashar, B. , and Shrivastava, J. , 1999. Data Preparation for Mining World Wide Web Browsing Patterns, Knowledge and Information Systems, 1
  11. Berendt, B. , Mobasher, B. , Spiliopoulou, M. , and Wiltshire, J. , 2001. Measuring the Accuracy of Sessionizers for Web Usage Analysis, Workshop on Web Mining at the First SIAM International Conference on Data Mining
  12. Mirjana Mazuran, Elisa Qunitarelli, and Latizia Tanca, ,IEEE Transactions on knowledge and Data Engineering, Vol. 24,No. 8, August 2012.
  13. World Wide Web Consortium, XQuery 1. 0: An XML Query language, http://www. w3c. org/TR/xquery,2007
  14. Arumuga Perumal, Integrating E-Commerece and cRM with Data Mining: A New Era, Journal of Internet Banking and Commerce, December 2005,Vol. 10,no. 3,http://www. arraydev. com/commerce/jibc/
  15. Ed Colet Approaches -DSstar Clustering and Classificatin –Data Mining.
  16. David L. Banks and Yasmin H. Said, Data Mining in Electronic Commerce, Statistical Science 2006,Vol. 21, No. 2,234-246,
  17. Fayadd, U. , Piatesky –Shapiro, G. , and Smyth, P "From Data Mining To Knowledge Discovery in Databases", AAAI Press / The MIT Press, Massachusetts Institute Of Technology. ISBN 0-26256097-6. MIT 1996
  18. Ralph Kimball, The Data Warehouse Toolkit:Practical Techniques for Building DimensionalData Warehouses, John Wiley & Sons,1996.
  19. Ralph Kimball, Laura Reeves, Margy Ross,Warren Thornthwaite, The Data WarehouseLifecycle Toolkit : Expert Methods for Designing,Developing, and Deploying DataWarehouses, John Wiley & Sons, 1998.
  20. Wand Frank, Na Helian, Yau Jim Yip , An Ecommerce System Integrating Data Mining Functionalities, IADIS International Conference, 2003.
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining e-Commerce e-Business CRM Issues Architecture Business Strategies