AAAI Publications, Twenty-First IAAI Conference

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Real-time Automatic Price Prediction for eBay Online Trading
Ilya Raykhel, Dan Ventura

Last modified: 2009-04-09


We develop a system for attribute-based prediction of final (online) auction pricing, focusing on the eBay laptop category. The system implements a feature-weighted k-NN algorithm, using evolutionary computation to determine feature weights, with prior trades used as training data. The resulting average prediction error is 16%.  Mostly automatic trading using the system greatly reduces the time a reseller needs to spend on trading activities, since the bulk of market research is now done automatically with the help of the learned model.  The result is a 562% increase in trading efficiency (measured as profit/hour).


Auctions and market-based systems; E-commerce; Information/mobile/software agents; Information extraction; Knowledge acquisition; Recommender systems; Web mining; Real-time systems; Data mining; Machine learning

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