Low Cost Journal,International Peer Reviewed and Refereed Journals,Fast Paper Publication approved journal IJEDR(ISSN 2321-9939) apply for ugc care approved journal, UGC Approved Journal, ugc approved journal, ugc approved list of journal, ugc care journal, care journal, UGC-CARE list, New UGC-CARE Reference List, UGC CARE Journals, ugc care list of journal, ugc care list 2020, ugc care approved journal, ugc care list 2020, new ugc approved journal in 2020, Low cost research journal, Online international research journal, Peer-reviewed, and Refereed Journals, scholarly journals, impact factor 7.37 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool)
INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH
(International Peer Reviewed,Refereed, Indexed, Citation Open Access Journal)
ISSN: 2321-9939 | ESTD Year: 2013

Current Issue

Call For Papers
March 2022

Volume 10 | Issue 1
Last Date : 29 March 2022
Review Results: Within 12-20 Days

For Authors

Archives

Indexing Partner

Research Area

LICENSE

Paper Details
Paper Title
Survey on Clustering of Massive Customer Transaction Data
Authors
  Mrs. Sonali L. Mortale,  Mrs. Manisha Darak

Abstract
Today a clustering of customer transaction data is very important procedure and to analyze customer behaviors in retail and e-commerce companies. Product from companies is organized as product tree, in which the leaf nodes are goods to sell, and the internal nodes (except root node) could be multiple product categories. We propose the “personalized product tree”, named purchase tree, to represent a customer’s transaction records. Customer’s transaction data set can be compressed into a set of purchase trees. We also propose a partitioned clustering algorithm, named PurTreeClust, for fast clustering of purchase trees. To cluster the purchase tree data, we first rank the purchase trees as candidate representative trees with a novel separate density, and then select the top k customers as the representatives of k customer groups. We also propose a gap statistic based method to evaluate the number of clusters. We use C 4.5 algorithm for making a decision tree, which can show different transaction of customer to make better purchase decision. Finally, the clustering results are obtained by assigning each customer to the nearest representative.

Keywords- Customer segmentation, clustering transaction data, purchase tree, clustering trees.
Publication Details
Unique Identification Number - IJEDR1804077
Page Number(s) - 419-421
Pubished in - Volume 6 | Issue 4 | December 2018
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Mrs. Sonali L. Mortale,  Mrs. Manisha Darak,   "Survey on Clustering of Massive Customer Transaction Data", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.6, Issue 4, pp.419-421, December 2018, Available at :http://www.ijedr.org/papers/IJEDR1804077.pdf
Share This Article


Article Preview

ISSN Details




DOI Details



Providing A digital object identifier by DOI
How to get DOI?

For Reviewer /Referral (RMS)

Important Links

NEWS & Conference

Digital Library

Our Social Link

© Copyright 2022 IJEDR.ORG All rights reserved