000 | 05030nam a22005055i 4500 | ||
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001 | 978-3-642-15606-9 | ||
003 | DE-He213 | ||
005 | 20140220084546.0 | ||
007 | cr nn 008mamaa | ||
008 | 101004s2010 gw | s |||| 0|eng d | ||
020 |
_a9783642156069 _9978-3-642-15606-9 |
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024 | 7 |
_a10.1007/978-3-642-15606-9 _2doi |
|
050 | 4 | _aTA329-348 | |
050 | 4 | _aTA640-643 | |
072 | 7 |
_aTBJ _2bicssc |
|
072 | 7 |
_aMAT003000 _2bisacsh |
|
082 | 0 | 4 |
_a519 _223 |
100 | 1 |
_aCasillas, Jorge. _eeditor. |
|
245 | 1 | 0 |
_aMarketing Intelligent Systems Using Soft Computing _h[electronic resource] : _bManagerial and Research Applications / _cedited by Jorge Casillas, Francisco J. Martínez-López. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010. |
|
300 |
_aXIV, 478 p. _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 |
||
490 | 1 |
_aStudies in Fuzziness and Soft Computing, _x1434-9922 ; _v258 |
|
505 | 0 | _aEssays -- Marketing and Artificial Intelligence: Great Opportunities, Reluctant Partners -- Data Mining and Scientific Knowledge: Some Cautions for Scholarly Researchers -- Observations on Soft Computing in Marketing -- Soft Computing Methods in Marketing: Phenomena and Management Problems -- User-Generated Content: The “Voice of the Customer” in the 21st Century -- Fuzzy Networks -- KDD: Applying in Marketing Practice Using Point of Sale Information -- Marketing – Sales Interface and the Role of KDD -- Segmentation and Targeting -- Applying Soft Cluster Analysis Techniques to Customer Interaction Information -- Marketing Intelligent System for Customer Segmentation -- Using Data Fusion to Enrich Customer Databases with Survey Data for Database Marketing -- Collective Intelligence in Marketing -- Marketing Modelling -- Predictive Modeling on Multiple Marketing Objectives Using Evolutionary Computation -- Automatic Discovery of Potential Causal Structures in Marketing Databases Based on Fuzzy Association Rules -- Fuzzy–Evolutionary Modeling of Customer Behavior for Business Intelligence -- Communication/Direct Marketing -- An Evaluation Model for Selecting Integrated Marketing Communication Strategies for Customer Relationship Management -- Direct Marketing Based on a Distributed Intelligent System -- Direct Marketing Modeling Using Evolutionary Bayesian Network Learning Algorithm -- Product -- Designing Optimal Products: Algorithms and Systems -- PRODLINE: Architecture of an Artificial Intelligence Based Marketing Decision Support System for PRODuct LINE Designs -- A Dempster-Shafer Theory Based Exposition of Probabilistic Reasoning in Consumer Choice -- E-Commerce -- Decision Making in Multiagent Web Services Based on Soft Computing -- Dynamic Price Forecasting in Simultaneous Online Art Auctions -- Analysing Incomplete Consumer Web Data Using the Classification and Ranking Belief Simplex (Probabilistic Reasoning and Evolutionary Computation). | |
520 | _aThe success of companies is partly dependent on the generation of suitable knowledge upon which to base decision-making, and due to the centrality of the marketing function in organizations, marketing-related knowledge is of strategic relevance. In this connection, it is unlikely to reach a full understanding of any set of systems supporting marketing management without paying the necessary attention to the Artificial Intelligence-based methodologies applied to aid marketing-related decisions. However, as yet these methods are both under-developed and under-used. This book represents a notable and creative step forward in this respect. The editorial project has especially focused on the so-called Marketing Intelligent Systems, a cutting-edge category for marketing management support that focuses on a sophisticated treatment of knowledge by Soft Computing and other machine learning techniques. The reader will find smart reflections on this general theme from diverse world-leading marketing academics through short essays, and a collection of chapters devoted to a variety of applications – segmentation, modeling, e-commerce, etc. – using different technologies such as clustering, evolutionary algorithms, multi-agent systems, or fuzzy logic. | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aArtificial intelligence. | |
650 | 0 | _aEngineering mathematics. | |
650 | 0 | _aMarketing. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aAppl.Mathematics/Computational Methods of Engineering. |
650 | 2 | 4 | _aArtificial Intelligence (incl. Robotics). |
650 | 2 | 4 | _aMarketing. |
700 | 1 |
_aMartínez-López, Francisco J. _eeditor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783642156052 |
830 | 0 |
_aStudies in Fuzziness and Soft Computing, _x1434-9922 ; _v258 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-15606-9 |
912 | _aZDB-2-ENG | ||
999 |
_c112678 _d112678 |