论文标题
使用交通指纹改善广告合格性
Improving Ads-Profitability Using Traffic-Fingerprints
论文作者
论文摘要
本文介绍了交通指纹的概念，即代表网页上每日流量分布的24维向量的归一化媒介。使用K-均值聚类我们表明，流量指纹的相似性与这些页面上显示的广告的获利时间模式相似。换句话说，这些指纹与转换率相关，从而使我们可以争论流量可忽略不计的页面上的转换率。通过阻止或解散整个页面，我们能够将在线活动的收入增加超过50％。
This paper introduces the concept of traffic-fingerprints, i.e., normalized 24-dimensional vectors representing a distribution of daily traffic on a web page. Using k-means clustering we show that similarity of traffic-fingerprints is related to the similarity of profitability time patterns for ads shown on these pages. In other words, these fingerprints are correlated with the conversions rates, thus allowing us to argue about conversion rates on pages with negligible traffic. By blocking or unblocking whole clusters of pages we were able to increase the revenue of online campaigns by more than 50%.
