A support system for predicting eBay end prices
Dennis van Heijst,
Rob Potharst and
Michiel van Wezel
No EI 2006-27, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute
Abstract:
In this report a support system for predicting end prices on eBay is proposed. 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.
Keywords: boosting; eBay; electronic auctions; text mining (search for similar items in EconPapers)
Date: 2006-10-25
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Persistent link: https://EconPapers.repec.org/RePEc:ems:eureir:8189
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