2007 PredictingClicks

　(Richardson et al., 2007) ⇒ Matthew Richardson, Ewa Dominowska, and Robert Ragno. (2007). “Predicting Clicks: estimating the click-through rate for new ads.” In: Proceedings of the 16th International Conference on World Wide Web (WWW 2007). doi:10.1145/1242572.1242643

Subject Headings Webclick Prediction, Clickthrough Rate.

Notes

Cited By

2016

(Juan et al., 2016) ⇒ Yuchin Juan, Yong Zhuang, Wei-Sheng Chin, and Chih-Jen Lin. (2016). “Field-aware Factorization Machines for CTR Prediction.” In: Proceedings of the 10th ACM Conference on Recommender Systems. ISBN:978-1-4503-4035-9 doi:10.1145/2959100.2959134
- QUOTE: ... Click-through rate (CTR) prediction plays an important role in advertising industry [ Chappele et al., 2015, McMahan et al., 2013, Richardson et al., 2007 ]. Logistic regression is probably the most widely used model for this task (Richardson et al., 2007). …

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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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2007 PredictingClicks	Matthew Richardson Ewa Dominowska Robert Ragno			Predicting Clicks: estimating the click-through rate for new ads		Proceedings of the 16th International Conference on World Wide Web	http://www2007.org/papers/paper784.pdf	10.1145/1242572.1242643		2007