A support system for predicting eBay end prices

作者:

摘要

We create a support system for predicting end prices on eBay. The end price predictions are based on the item descriptions found in the item listings of eBay, and on some numerical item features. The system uses text mining and boosting algorithms from the field of machine learning. Our system substantially outperforms the naive method of predicting the category mean price. Moreover, interpretation of the model enables us to identify influential terms in the item descriptions and shows that the item description is more influential than the seller feedback rating, which was shown to be influential in earlier studies.

论文关键词:Boosting,eBay,Electronic auctions,Text mining

论文评审过程:Received 25 October 2006, Revised 18 October 2007, Accepted 14 November 2007, Available online 22 November 2007.

论文官网地址:https://doi.org/10.1016/j.dss.2007.11.004