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Improving customer churn prediction by data augmentation using pictorial stimulus-choice data

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Table of Contents

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    Book Overview
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    Chapter 1 A Strategic Perspective on Management Intelligent Systems
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    Chapter 2 Visualization of Agents and Their Interaction within Dynamic Environments
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    Chapter 3 Hybrid Genetic-Fuzzy System Modeling Application in Innovation Management
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    Chapter 4 Using Data Mining and Vehicular Networks to Estimate the Severity of Traffic Accidents
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    Chapter 5 ContextCare: Autonomous Video Surveillance System Using Multi-camera and Smartphones
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    Chapter 6 Clustering of Fuzzy Cognitive Maps for Travel Behavior Analysis
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    Chapter 7 Smart Objects System: A Generic System for Enhancing Operational Control
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    Chapter 8 Distributed Cognition Learning in Collaborative Civil Engineering Projects Management
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    Chapter 9 Designing Lines of Cars That Optimize the Degree of Differentiation vs. Commonality among Models in the Line: A Natural Intelligence Approach
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    Chapter 10 Semantic Web Mining for Book Recommendation
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    Chapter 11 An Automated Approach to Product Taxonomy Mapping in E-Commerce
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    Chapter 12 A Case-Based Planning Mechanism for a Hardware-Embedded Reactive Agents Platform
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    Chapter 13 A Linguistic Approach for Semantic Web Service Discovery
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    Chapter 14 Applying Multi-objective Optimization for Variable Selection to Analyze User Trust in Electronic Banking
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    Chapter 15 A Context-Aware Mobile Recommender System Based on Location and Trajectory
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    Chapter 16 Mark i S: A Marketing Intelligent System Software Application for Causal Modeling
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    Chapter 17 Prosaico: An Intelligent System for the Management of a Sports Facility
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    Chapter 18 Automatic Extraction of the Real Organizational Hierarchy Using JADE
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    Chapter 19 Integration of a Proximity Detection Prototype into a VO Developed with PANGEA
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    Chapter 20 Approximating the Pareto-front of Continuous Bi-objective Problems: Application to a Competitive Facility Location Problem
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    Chapter 21 Improving Customer Churn Prediction by Data Augmentation Using Pictorial Stimulus-Choice Data
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    Chapter 22 A Multiple-Agent Based System for Forecasting the Ice Cream Demand Using Climatic Information
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    Chapter 23 Manual Intervention and Statefulness in Agent-Involved Workflow Management Systems
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    Chapter 24 A Statistical Approach to Star Rating Classification of Sentiment
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    Chapter 25 Non-parametric Statistical Analysis of Machine Learning Methods for Credit Scoring
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    Chapter 26 Rule-Based Business Process Mining: Applications for Management
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    Chapter 27 A News-Based Approach for Computing Historical Value-at-Risk
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    Chapter 28 Gaussian Mixture Models vs. Fuzzy Rule-Based Systems for Adaptive Meta-scheduling in Grid/Cloud Computing
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    Chapter 29 Reduced Large Datasets by Fuzzy C-Mean Clustering Using Minimal Enclosing Ball
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    Chapter 30 Impact of Initial Tuning for Algorithm That Solve Query Routing
  32. Altmetric Badge
    Chapter 31 Developing Anti-spam Filters Using Automatically Generated Rough Sets Rules
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Title
Improving customer churn prediction by data augmentation using pictorial stimulus-choice data
Published by
Springer, January 2012
DOI 10.1007/978-3-642-30864-2
ISBNs
978-3-64-230863-5, 978-3-64-230864-2
Authors

Ballings, Michel, Van den Poel, Dirk, Verhagen, Emmanuel

Editors

Casillas, Jorge, Martínez-López, Francisco J., Corchado Rodríguez, Juan Manuel

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 5%
Unknown 21 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 23%
Student > Master 4 18%
Researcher 4 18%
Student > Postgraduate 2 9%
Student > Bachelor 2 9%
Other 5 23%
Readers by discipline Count As %
Computer Science 12 55%
Business, Management and Accounting 4 18%
Economics, Econometrics and Finance 1 5%
Unspecified 1 5%
Earth and Planetary Sciences 1 5%
Other 3 14%