Emerging Application or Methodologies Papers
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%. Â 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. Â The result is a 562% increase in trading efficiency (measured as profit/hour).