JOURNAL ARTICLE

Market Basket Analysis with Data Mining methods

Abstract

This paper describes the way of Market Basket Analysis implementation to Six Sigma methodology. Data Mining methods provide a lot of opportunities in the market sector. Basket Market Analysis is one of them. Six Sigma methodology uses several statistical methods. With implementation of Market Basket Analysis (as a part of Data Mining) to Six Sigma (to one of its phase), we can improve the results and change the Sigma performance level of the process. In our research we used GRI (General Rule Induction) algorithm to produce association rules between products in the market basket. These associations show a variety between the products. To show the dependence between the products we used a Web plot. The last algorithm in analysis was C5.0. This algorithm was used to build rule-based profiles.

Keywords:
Affinity analysis Six Sigma Computer science Data mining Association rule learning Market analysis Process (computing) Sigma Engineering Business Manufacturing engineering

Metrics

31
Cited By
2.08
FWCI (Field Weighted Citation Impact)
11
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Big Data and Business Intelligence
Social Sciences →  Business, Management and Accounting →  Management Information Systems
Data Mining Algorithms and Applications
Physical Sciences →  Computer Science →  Information Systems
Fuzzy Logic and Control Systems
Physical Sciences →  Computer Science →  Artificial Intelligence

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