Knowledge discovery on consumers' behaviour

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F13%3A00213762" target="_blank" >RIV/62156489:43110/13:00213762 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Knowledge discovery on consumers' behaviour

Original language description

This paper summarizes results of the research project "Application of modern methods to data processing in the field of marketing research" which was solved at the Department of Informatics, Faculty of Business and Economics of Mendel University in Brno.The most of these results were presented at international conferences. It describes the use of knowledge discovery techniques on data from marketing research of consumers' behaviour. The paper deals with issues of classification, cluster analysis, correlation and association rules. For classification there were used various algorithms: multi-layer perceptron neural network, self-organizing (Kohonen's) maps, bayesian networks and generation of a decision tree. Beside Kohonen's maps, which were tested inMATLAB software, all classification methods were tested in Weka software. In order to find clusters of the methods K-means, Expectation-Maximization, DBSCAN Weka was also used as software for clustering. Correlation analysis was done bas

Czech name

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Czech description

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Type

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

CEP classification

AE - Management, administration and clerical work

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2013

Confidentiality

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

Name of the periodical

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis

ISSN

1211-8516

e-ISSN

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Volume of the periodical

61

Issue of the periodical within the volume

7

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

9

Pages from-to

2893-2901

UT code for WoS article

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EID of the result in the Scopus database

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