Feature hashing for large scale multitask learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Data-driven text features for sponsored search click prediction
Proceedings of the Third International Workshop on Data Mining and Audience Intelligence for Advertising
Using boosted trees for click-through rate prediction for sponsored search
Proceedings of the Sixth International Workshop on Data Mining for Online Advertising and Internet Economy
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Click prediction for sponsored search is an important problem for commercial search engines. Good click prediction algorithm greatly affects on the revenue of the search engine, user experience and brings more clicks to landing pages of advertisers. This paper presents new query-dependent features for the click prediction algorithm based on treating query and advertisement as bags of words. New features can improve prediction accuracy both for ads having many and few views.