C4.5: programs for machine learning
C4.5: programs for machine learning
Case-based reasoning
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Inside Case-Based Reasoning
Improved use of continuous attributes in C4.5
Journal of Artificial Intelligence Research
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The French credit card system makes it highly profitable for banks to have heavily used Automated Teller Machines (ATM). "La Caisse d'Épargne", one of the major French bank manages 5000 ATMs allover France. The goal of the Sthana system is to capitalize the knowledge spread all over the company into a system capable of issuing recommendations for existing ATM's and capable of forecasting a new ATM's activity. Sthana uses Data Mining and Case-Based-Reasoning techniques so as to extract information from existing data (including economic, geographical and internal bank data) and from the bank's ATM experts. The system builds up classifications on high level descriptors from raw data and eventually indicates a measure of the ATM's activity and profitability, highlights factors which could lead to higher profitability or pinpoints the ATM's vulnerabilities. An objectoriented model coupled with an extremely modular system allows the data and rules to be customized for geographical units of the bank. Sthana has been deployed and customized for different geographical units, but the knowledge base is centralized in the bank headquarters in Paris.