Manuscript Number : CSEIT183564
Generating Association rules to identify frequent patterns in E-Commerce
Authors(2) :-P. Regina, Prof. M. V. Ramana Murthy Internet emerged as one of the important tools of communication in the recent years and E-commerce has gradually grown with it and has given rise to a new world of doing business. It has drawn attention to apply data mining techniques to identify frequent patterns for improving business strategies. The main aim of Frequent pattern discovery is to find frequently occurring itemsets in large databases. Frequent pattern mining is the most important step in mining association rules to show items that have same patterns in the database, appear together. In E-commerce, frequently occurring product purchase combinations are essential to model user preference. In this paper we look at the existing algorithms which are used to identify the association rules and discusses how they are extend to find frequent patterns in E-commerce.
P. Regina Frequent pattern discovery, association rules, E-commerce Publication Details Published in : Volume 3 | Issue 5 | May-June 2018 Article Preview
Research Scholar, Department. of CSE, Dravidian University, Kuppam, Aurora's PG college, Uppal, Hyderabad, Telangana, India
Prof. M. V. Ramana Murthy
Professor & Head of Mathematics & IT, MGIT, Hyderabad, Telangana, India
Date of Publication : 2018-06-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 240-243
Manuscript Number : CSEIT183564
Publisher : Technoscience Academy