BOOK-CHAPTER

Data Mining in Marketing Using Bayesian Networks and Evolutionary Programming

Geng CuiMan Leung Wong

Year: 2002 Studies in fuzziness and soft computing Pages: 198-214   Publisher: Springer Nature

Abstract

Give the explosive growth of customer data collected electronically from current electronic business environment, data mining can potentially discover new knowledge to improve managerial decision making in marketing. This study proposes an innovative approach to data mining using Bayesian Networks and evolutionary programming and applies the methods to marketing data. The results suggest that this approach to knowledge discovery can generate superior results than the conventional method of logistic regression. Future research in this area should devote more attention to applying this and other data mining methods to solving complex problems facing today's electronic businesses.

Keywords:
Computer science Bayesian network Bayesian probability Data mining Data science Explosive material Logistic regression Knowledge extraction Machine learning Artificial intelligence Geography

Metrics

1
Cited By
0.00
FWCI (Field Weighted Citation Impact)
27
Refs
0.06
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Data Mining Algorithms and Applications
Physical Sciences →  Computer Science →  Information Systems
Bayesian Modeling and Causal Inference
Physical Sciences →  Computer Science →  Artificial Intelligence
Evolutionary Algorithms and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence

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