Offline Evaluation Of Response Prediction In Online Advertising Auctions
WWW '15: 24th International World Wide Web Conference Florence Italy May, 2015(2015)
摘要
Click-through rates and conversion rates are two core machine learning problems in online advertising. The evaluation of such systems is often based on traditional supervised learning metrics that ignore how the predictions are used. These predictions are in fact part of bidding systems in online advertising auctions. We present here an empirical evaluation of a metric that is specifically tailored for auctions in online advertising and show that it correlates better than standard metrics with A/B test results.
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关键词
Online advertising,auction,response prediction,metrics
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