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...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
2003
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/8705/1/FSKTM_2003_7%20IR.pdf http://psasir.upm.edu.my/id/eprint/8705/ |
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| Summary: | 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. |
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