Improving web search ranking by incorporating user behavior information
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Predicting clicks: estimating the click-through rate for new ads
Proceedings of the 16th international conference on World Wide Web
Predicting bounce rates in sponsored search advertisements
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
"TV answers" - using the wisdom of crowds to facilitate searches with rich media context
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
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This paper explores the impact of television advertisements on audience retention using data collected from television set-top boxes (STBs). In particular, we discuss how the accuracy of the retention score, a measure of ad quality, is improved by using the recent "click history" of the STBs tuned to the ad. These retention scores are related to -- and are a natural extension of -- other measures of ad quality that have been used in online advertising since at least 2005 [2]. Like their online counterparts, TV retention scores could be used to determine if an ad should be eligible to enter the inventory auction and, if it is, how highly the ad should be ranked [1]. A retention score (RS) could also be used by the auction system for pricing, or by the advertiser to compare different creatives for the same product.