We present a knowledge discovery case study on customer classification having the objective of mining the distinctive characteristics of new customers of a service of tax return. Two general approaches are described. The first one, a symbolic approach, is based on extracting and ranking classification rules on the basis of significativeness measures defined on the 4-fold contingency table of a rule. The second one, a spatial approach, is based on extracting geographic areas with predominant presence of new customers.

Who/where are my new customers?

Rinzivillo Salvatore;Ruggieri Salvatore
2011

Abstract

We present a knowledge discovery case study on customer classification having the objective of mining the distinctive characteristics of new customers of a service of tax return. Two general approaches are described. The first one, a symbolic approach, is based on extracting and ranking classification rules on the basis of significativeness measures defined on the 4-fold contingency table of a rule. The second one, a spatial approach, is based on extracting geographic areas with predominant presence of new customers.
2011
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
Inglese
Dominik Ry?ko, Henryk Rybi?ski, Piotr Gawrysiak, Marzena Kryszkiewicz
Emerging Intelligent Technologies in Industry
307
317
978-3-642-22731-8
http://link.springer.com/chapter/10.1007%2F978-3-642-22732-5_25
Springer-Verlag
Berlin/Heidelberg
GERMANIA
classification rules
interestingness measures
spatial classificat
spatial visualization
ID PUMA: cnr.isti/2011-A1-041
2
02 Contributo in Volume::02.01 Contributo in volume (Capitolo o Saggio)
268
restricted
Rinzivillo, Salvatore; Ruggieri, Salvatore
info:eu-repo/semantics/bookPart
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/179643
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