Simple Search:

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


Citation

Abdul Kadir, Khairil Annuar (2003) Clustering Algorithm for Market-Basket Analysis: The Underlying Concept of Data Mining Technology. Masters thesis, Universiti Putra Malaysia.

Abstract / Synopsis

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.


Download File

[img] PDF
FSKTM_2003_7_A.pdf

Download (437kB)

Additional Metadata

Item Type: Thesis (Masters)
Subject: Data mining
Subject: Cluster analysis - Computer programs
Call Number: FSKTM 2003 7
Chairman Supervisor: Professor Madya Dr. Md. Nasir b. Sulaiman
Divisions: Faculty of Computer Science and Information Technology
Depositing User: Nurul Hayatie Hashim
Date Deposited: 15 Dec 2010 12:54
Last Modified: 12 Dec 2012 13:20
URI: http://psasir.upm.edu.my/id/eprint/8705
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item