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Clustering Algorithm for Market-Basket Analysis: The Underlying Concept of Data Mining Technology

The goal of data mining is to extract interesting correlated 
information from large databases. This thesis seeks to 
understand the underlying concept of data mining technology in 
market-basket analysis. The clustering algorithm based on 
Small Large Ratios, SLR is presented in a manner that helps to 
understand the concept of data mining technology in marketbasket 
analysis. The author used a data mining software called 
PolyAnalyst 4.5 to perform analysis on the set of items that 
customers have bought in supermarket for market-basket 
application. In this research, the author tried to relate the 
algorithm presented with the experiment. Then, the author 
discussed the results by showing an application of marketbasket 
analysis. The statistical results from the PolyAnalyst's 
reports are explained and elaborated further i n the results 
section. The author summarized the findings and tried to relate 
them to the benefits of data mining towards organizations.