2007 PredictingClicks

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Subject Headings Webclick Prediction, Clickthrough Rate.

Notes

Cited By

2016

Quotes

Author Keywords

click-through rate, sponsored search, paid search, Web advertising, CTR, CPC, ranking.

Abstract

Search engine advertising has become a significant element of the Web browsing experience. Choosing the right ads for the query and the order in which they are displayed greatly affects the probability that a user will see and click on each ad. This ranking has a strong impact on the revenue the search engine receives from the ads. Further, showing the user an ad that they prefer to click on improves user satisfaction. For these reasons, it is important to be able to accurately estimate the click-through rate of ads in the system. For ads that have been displayed repeatedly, this is empirically measurable, but for new ads, other means must be used. We show that we can use features of ads, terms, and advertisers to learn a model that accurately predicts the click-through rate for new ads. We also show that using our model improves the convergence and performance of an advertising system. As a result, our model increases both revenue and user satisfaction.


References


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2007 PredictingClicksMatthew Richardson
Ewa Dominowska
Robert Ragno
Predicting Clicks: estimating the click-through rate for new adsProceedings of the 16th International Conference on World Wide Webhttp://www2007.org/papers/paper784.pdf10.1145/1242572.12426432007