TY  - BOOK
AU  - Kaufmann,Michael
ED  - SpringerLink (Online service)
TI  - Inductive Fuzzy Classification in Marketing Analytics
T2  - Fuzzy Management Methods,
SN  - 9783319058610
AV  - HF54.5-54.56 
U1  - 650 23
PY  - 2014///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Economics
KW  - Computer Science
KW  - Data mining
KW  - Marketing
KW  - Management information systems
KW  - Economics/Management Science
KW  - Business Information Systems
KW  - Data Mining and Knowledge Discovery
KW  - Mathematical Logic and Formal Languages
KW  - Information Systems Applications (incl. Internet)
KW  - e-Commerce/e-business
N1  - A Gradual Concept of Truth -- Fuzziness and Induction -- Analytics and Marketing -- Prototyping and Evaluation -- Precisiating Fuzziness by Induction
N2  - To enhance marketing analytics, approximate and inductive reasoning can be applied to handle uncertainty in individual marketing models. This book demonstrates the use of fuzzy logic for classification and segmentation in marketing campaigns. Based on practical experience as a data analyst and on theoretical studies as a researcher, the author explains fuzzy classification, inductive logic, and the concept of likelihood, and introduces a blend of Bayesian and Fuzzy Set approaches, allowing reasonings on fuzzy sets that are derived by inductive logic. By application of this theory, the book guides the reader towards a gradual segmentation of customers which can enhance return on targeted marketing campaigns. The algorithms presented can be used for visualization, selection and prediction. The book shows how fuzzy logic can complement customer analytics by introducing fuzzy target groups. This book is for researchers, analytics professionals, data miners and students interested in fuzzy classification for marketing analytics
UR  - http://dx.doi.org/10.1007/978-3-319-05861-0
ER  -