Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Predicting clicks: estimating the click-through rate for new ads
Proceedings of the 16th international conference on World Wide Web
Estimating advertisability of tail queries for sponsored search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Learning to advertise: how many ads are enough?
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
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Click Through Rate (CTR) is an important metric for ad systems, job portals, recommendation systems. CTR impacts publisher's revenue, advertiser's bid amounts in "pay for performance" business models. We learn regression models using features of the job, optional click history of job, features of "related" jobs. We show that our models predict CTR much better than predicting avg. CTR for all job listings, even in absence of the click history for the job listing.