Mining the Client's Life Cycle Behaviour in the Web
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Cost-based labeling of groups of mass spectra
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Data mining of Bayesian networks using cooperative coevolution
Decision Support Systems
Learning Bayesian networks from incomplete databases using a novel evolutionary algorithm
Decision Support Systems
Blending e-learning and knowledge management for optimizing learning paths
AIKED'08 Proceedings of the 7th WSEAS International Conference on Artificial intelligence, knowledge engineering and data bases
Hybrid Repayment Prediction for Debt Portfolio
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Prediction of Sequential Values for Debt Recovery
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Decreasing time response of e-Learning platforms by expertise acquisition
EuroIMSA '08 Proceedings of the IASTED International Conference on Internet and Multimedia Systems and Applications
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
A hybrid intelligent system for generic decision for PID controllers design in open-loop
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
A Joint Model of Usage and Churn in Contractual Settings
Marketing Science
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From the Publisher:Increase profits and reduce costs by utilizing this collection of models of the most commonly asked data mining questionsIn order to find new ways to improve customer sales and support, and as well as manage risk, business managers must be able to mine company databases. This book provides a step-by-step guide to creating and implementing models of the most commonly asked data mining questions. Readers will learn how to prepare data to mine, and develop accurate data mining questions. The author, who has over ten years of data mining experience, also provides actual tested models of specific data mining questions for marketing, sales, customer service and retention, and risk management. A CD-ROM, sold separately, provides these models for reader use.