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Forecasting Winning Bid Prices on an Online Auction Market - Data Mining Approaches -
Authors:KIM Hongil  BAEK Seung
Institution:1.College of Business Administration,Hanyang University Seoul 133-791 Korea
Abstract:To solve information asymmetry problem on online auction, this study suggests and validates a forecasting model of winning bid prices. Especially, it explores the usability of data mining approaches, such as neural network and Bayesian network in building a forecasting model. This research empirically shows that, in forecasting winning bid prices on online auction, data mining techniques have showed better performance than traditional statistical analysis, such as logistic regression and multivariate regression.
Keywords:Bayesian network  data mining  neural network  price forecasting
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