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- W1494095829 abstract "In the past, some sites selected for closure by a large international bank in Hong Kong were based on personal experience of a group of experts by formulating a set of evaluation guidelines. The current 300 existing sites are therefore considered to represent a set of rules and expert decisions which are manually recorded on paper files and de-centralized. In order to validate the guidelines/rules and discover any hidden knowledge, we employ a data mining approach to examine the data comprehensively. Several modeling techniques including neural network, C5.0 and General Rule Induction systems are used to determine the significance of those attributes in the data set. Various models based on the historical data set of sites in different forms are constructed to deduce a rule-based model for subsequent use. Promising result has been obtained which can be applied in future Branch and ATM Site Evaluation with a view of providing a better solution. The useful patterns and knowledge discovered will further add benefit to exploring customer intelligence and devising marketing planning strategies." @default.
- W1494095829 created "2016-06-24" @default.
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- W1494095829 date "2006-01-01" @default.
- W1494095829 modified "2023-10-16" @default.
- W1494095829 title "A Data Mining Approach for Branch and ATM Site Evaluation" @default.
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- W1494095829 doi "https://doi.org/10.1007/11677437_24" @default.
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