广告是竞争还是合作?:设计包含完整关系的点击模型

Xin Xin, Irwin King, Ritesh Agrawal, Michael R. Lyu, Heyan Huang
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引用次数: 1

摘要

传统的点击模型预测广告(广告)的点击率(CTR)独立于其他广告。然而,最近的研究表明,广告的点击率不仅取决于广告本身的质量,还取决于邻近广告的质量。使用商业广告服务器的历史点击率数据,我们确定了赞助广告之间的两种类型(竞争和协作)的影响,并进一步提出了一种新的点击模型,全关系模型(FRM)。在测试数据上,与早期的点击模型相比,FRM在点击率预测方面显示出显着的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Do ads compete or collaborate?: designing click models with full relationship incorporated
Traditionally click models predict click-through rate (CTR) of an advertisement (ad) independent of other ads. Recent researches however indicate that the CTR of an ad is dependent on the quality of the ad itself but also of the neighboring ads. Using historical click-through data of a commercially available ad server, we identify two types (competing and collaborating) of influences among sponsored ads and further propose a novel click-model, Full Relation Model (FRM), which explicitly models dependencies between ads. On a test data, FRM shows significant improvement in CTR prediction as compared to earlier click models.
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