Marketing intelligent systems using soft computing
著者
書誌事項
Marketing intelligent systems using soft computing
（Studies in fuzziness and soft computing, 258）
Springer, c2010
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内容説明・目次
内容説明
Dr. Jay Liebowitz Orkand Endowed Chair in Management and Technology University of Maryland University College Graduate School of Management & Technology 3501 University Boulevard East Adelphi, Maryland 20783-8030 USA jliebowitz@umuc. edu When I first heard the general topic of this book, Marketing Intelligent Systems or what I'll refer to as Marketing Intelligence, it sounded quite intriguing. Certainly, the marketing field is laden with numeric and symbolic data, ripe for various types of mining-data, text, multimedia, and web mining. It's an open laboratory for applying numerous forms of intelligentsia-neural networks, data mining, expert systems, intelligent agents, genetic algorithms, support vector machines, hidden Markov models, fuzzy logic, hybrid intelligent systems, and other techniques. I always felt that the marketing and finance domains are wonderful application areas for intelligent systems, and this book demonstrates the synergy between marketing and intelligent systems, especially soft computing. Interactive advertising is a complementary field to marketing where intelligent systems can play a role. I had the pleasure of working on a summer faculty f- lowship with R/GA in New York City-they have been ranked as the top inter- tive advertising agency worldwide. I quickly learned that interactive advertising also takes advantage of data visualization and intelligent systems technologies to help inform the Chief Marketing Officer of various companies. Having improved ways to present information for strategic decision making through use of these technologies is a great benefit.
目次
Essays.- 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).
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