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035   $a(DE-He213)978-3-319-05861-0
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100   $a20140604d2014      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aInductive Fuzzy Classification in Marketing Analytics /$fby Michael Kaufmann
205   $a1st ed. 2014.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014.
215   $a1 online resource (143 p.)
225 1 $aFuzzy Management Methods,$x2196-4130
300   $aDescription based upon print version of record.
311   $a1-322-13473-1 
311   $a3-319-05860-6 
320   $aIncludes bibliographical references.
327   $aA Gradual Concept of Truth -- Fuzziness and Induction -- Analytics and Marketing -- Prototyping and Evaluation -- Precisiating Fuzziness by Induction.
330   $aTo enhance marketing analytics, approximate and inductive reasoning can be applied to handle uncertainty in individual marketing models. This book demonstrates the use of fuzzy logic for classification and segmentation in marketing campaigns. Based on practical experience as a data analyst and on theoretical studies as a researcher, the author explains fuzzy classification, inductive logic, and the concept of likelihood, and introduces a blend of Bayesian and Fuzzy Set approaches, allowing reasonings on fuzzy sets that are derived by inductive logic. By application of this theory, the book guides the reader towards a gradual segmentation of customers which can enhance return on targeted marketing campaigns. The algorithms presented can be used for visualization, selection and prediction. The book shows how fuzzy logic can complement customer analytics by introducing fuzzy target groups. This book is for researchers, analytics professionals, data miners and students interested in fuzzy classification for marketing analytics.
410  0$aFuzzy Management Methods,$x2196-4130
606   $aInformation technology
606   $aBusiness?Data processing
606   $aData mining
606   $aMarketing
606   $aMathematical logic
606   $aApplication software
606   $aE-commerce
606   $aIT in Business$3https://scigraph.springernature.com/ontologies/product-market-codes/522000
606   $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030
606   $aMarketing$3https://scigraph.springernature.com/ontologies/product-market-codes/513000
606   $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048
606   $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040
606   $ae-Commerce/e-business$3https://scigraph.springernature.com/ontologies/product-market-codes/I26000
615  0$aInformation technology.
615  0$aBusiness?Data processing.
615  0$aData mining.
615  0$aMarketing.
615  0$aMathematical logic.
615  0$aApplication software.
615  0$aE-commerce.
615 14$aIT in Business.
615 24$aData Mining and Knowledge Discovery.
615 24$aMarketing.
615 24$aMathematical Logic and Formal Languages.
615 24$aInformation Systems Applications (incl. Internet).
615 24$ae-Commerce/e-business.
676   $a658.800151
700   $aKaufmann$b Michael$4aut$4http://id.loc.gov/vocabulary/relators/aut$01065100
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910298557703321
996   $aInductive Fuzzy Classification in Marketing Analytics$92543174
997   $aUNINA