000 | 03141nam a22006015i 4500 | ||
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001 | 978-3-319-05861-0 | ||
003 | DE-He213 | ||
005 | 20200420211749.0 | ||
007 | cr nn 008mamaa | ||
008 | 140604s2014 gw | s |||| 0|eng d | ||
020 |
_a9783319058610 _9978-3-319-05861-0 |
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024 | 7 |
_a10.1007/978-3-319-05861-0 _2doi |
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050 | 4 | _aHF54.5-54.56 | |
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_aKJQ _2bicssc |
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_aBUS083000 _2bisacsh |
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_aCOM039000 _2bisacsh |
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082 | 0 | 4 |
_a650 _223 |
082 | 0 | 4 |
_a658.05 _223 |
100 | 1 |
_aKaufmann, Michael. _eauthor. |
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245 | 1 | 0 |
_aInductive Fuzzy Classification in Marketing Analytics _h[electronic resource] / _cby Michael Kaufmann. |
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2014. |
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300 |
_aXX, 125 p. 35 illus. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aFuzzy Management Methods, _x2196-4130 |
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505 | 0 | _aA Gradual Concept of Truth -- Fuzziness and Induction -- Analytics and Marketing -- Prototyping and Evaluation -- Precisiating Fuzziness by Induction. | |
520 | _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. | ||
650 | 0 | _aBusiness. | |
650 | 0 | _aMarketing. | |
650 | 0 | _aInformation technology. | |
650 | 0 |
_aBusiness _xData processing. |
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650 | 0 | _aMathematical logic. | |
650 | 0 | _aData mining. | |
650 | 0 | _aE-commerce. | |
650 | 1 | 4 | _aBusiness and Management. |
650 | 2 | 4 | _aIT in Business. |
650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
650 | 2 | 4 | _aMarketing. |
650 | 2 | 4 | _aMathematical Logic and Formal Languages. |
650 | 2 | 4 | _aInformation Systems Applications (incl. Internet). |
650 | 2 | 4 | _ae-Commerce/e-business. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783319058603 |
830 | 0 |
_aFuzzy Management Methods, _x2196-4130 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-05861-0 |
912 | _aZDB-2-SBE | ||
942 | _cEBK | ||
999 |
_c51180 _d51180 |