• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Real-Time Data Analytics and Optimization for Computational Advertising
【24h】

Real-Time Data Analytics and Optimization for Computational Advertising

机译：计算广告的实时数据分析和优化

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Online advertising has built a market of hundreds of billions of dollars and still continues to grow. With well developed techniques in big data storage, data mining and analytics, online advertising is able to reach targeted audiences e?ctively. Real-time bidding refers to the buying and selling of online ad impressions through ad inventory auctions which occur in the time it takes a webpage to load. How to determine the bidding price and how to allocate the budget of advertising is the key to successful ad campaigns. Both of these aspects are fundamental to most campaign optimizations and we will introduce both of them in this thesis. For bidding price determination, we improved the estimation of CTR (Click Through Rate) (one of the most important factors of determining the bidding price) by using a re?ned hierarchical tree structure for the estimation. The result of the experiment and the A/B test showed our proposal can provide stable improvement. For budget allocation, we introduce SCO (Single Campaign Optimization) and CCO (Cross Campaign Optimization). SCO has been applied by our commercial partner while CCO needs more research. We will ?rst introduce the methods of SCO and then give our proposal about CCO. We modeled CCO as a LP (Linear Programming) problem as well as designed an e?ective procedure to implement optimal impressions distribution. Our simulation showed our proposal can signi?cantly increase global Gross Pro?t (GP).
机译：在线广告已经建立了数千亿美元的市场，并且仍在继续增长。借助大数据存储，数据挖掘和分析中成熟的技术，在线广告能够有效地覆盖目标受众。实时出价是指通过广告资源拍卖来进行的在线广告印象的买卖，这是在加载网页时发生的。如何确定标价和如何分配广告预算是成功开展广告活动的关键。这两个方面都是大多数广告系列优化的基础，我们将在本文中介绍这两个方面。对于投标价格的确定，我们通过使用改进的分层树结构来估计CTR（点击率）（确定投标价格的最重要因素之一），从而提高了估算值。实验结果和A / B测试表明我们的建议可以提供稳定的改进。对于预算分配，我们介绍了SCO（单个广告系列优化）和CCO（交叉广告系列优化）。 SCO已被我们的商业伙伴采用，而CCO需要更多的研究。我们将首先介绍SCO的方法，然后提出有关CCO的建议。我们将CCO建模为LP（线性编程）问题，并设计了一种有效的程序来实现最佳的印象分配。模拟结果表明，我们的建议可以显着提高全球总利润（GP）。

著录项

  • 作者

    Liu, Hui.;

  • 作者单位

    Florida Atlantic University.;

  • 授予单位 Florida Atlantic University.;
  • 学科 Computer science.
  • 学位 M.S.
  • 年度 2017
  • 页码 71 p.
  • 总页数 71
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号