In their effort to incorporate electronic commerce capabilities, many organizations have established comprehensive data warehouses to integrate operational data with customers, suppliers, and other channel partners. Emerging data mining techniques enable organizations to prioritize and structure information from these warehouses. Through its discovery of changes, associations, rules, anomalies, and patterns, data mining can lead to significant business benefits when combined with current information systems. This chapter illustrates the pivotal role that data mining plays in an electronic commerce environment by highlighting two case studies in which neural network-based data mining techniques were used for inventory optimization. Issues such as automated identification of input-output lags, data augmentation, and optimal neural network architectures are discussed.
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