Data Mining in Practice: Customer Segmentation by Purchasing Behavior

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F11%3A53261" target="_blank" >RIV/60460709:41110/11:53261 - isvavai.cz</a>

Result on the web

—

DOI - Digital Object Identifier

—

Result language

čeština

Original language name

Data mining v praxi: segmentace zákazníků dle nákupního chování

Original language description

The aim of this paper was to find and evaluate the different methodological approaches appropriate for customer segmentation. Various data mining techniques were used for demonstration of customer segmentation according to their purchasing behavior within a selected hypermarket. The following techniques were used for clustering: K-means clustering method, Two Step clustering method and Self Organizing Maps. The quality of final models was evaluated by Silhouette measure that combines the principles of clusters separation and cohesion. Data mining model was constructed from approximately 60 thousand transaction records. Only the food records were selected for the analysis.

Czech name

Data mining v praxi: segmentace zákazníků dle nákupního chování

Czech description

The aim of this paper was to find and evaluate the different methodological approaches appropriate for customer segmentation. Various data mining techniques were used for demonstration of customer segmentation according to their purchasing behavior within a selected hypermarket. The following techniques were used for clustering: K-means clustering method, Two Step clustering method and Self Organizing Maps. The quality of final models was evaluated by Silhouette measure that combines the principles of clusters separation and cohesion. Data mining model was constructed from approximately 60 thousand transaction records. Only the food records were selected for the analysis.

Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BB - Applied statistics, operational research

OECD FORD branch

—

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2011

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Scientific Papers of the University of Pardubice. Series D. Faculty of Economics and Administration

ISSN

1211-555X

e-ISSN

—

Volume of the periodical

20

Issue of the periodical within the volume

2

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

11

Pages from-to

135-145

UT code for WoS article

—

EID of the result in the Scopus database

—