Support System for Predicting Online Auction End Prices

Abstract

By analyzing bidders' behaviors, the author proposed a new model which is based on the Bagging arithmetic and decision tree for predicting final prices of online auctions. The author collected 3310 transaction data and corresponding 8275 bids from Taobao. Data analysis shows that the final prices of 40.4% transactions can be calculated by using the times of bids. Instead of predicting the final price directly, the author predicts times of bids first and then used it to calculate the final price. The experiment proves that the model substantially outperforms the naive method of predicting the category mean price, and 21.7% of predicted results are exactly equal to the real ones. Compared with Heijst's research, the model is better in required training sample size, calculating time and percentage of accurate prediction. For training, time is only a few seconds, this research can lay the foundation for developping real-time dectsion support systems.