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AiAds: Automated and Intelligent Advertising System for Sponsored Search

机译:AIADS:自动化和智能广告系统的赞助搜索

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Sponsored search has more than 20 years of history, and it has been proven to be a successful business model for online advertising. Based on the pay-per-click pricing model and the keyword targeting technology, the sponsored system runs online auctions to determine the allocations and prices of search advertisements. In the traditional setting, advertisers should manually create lots of ad creatives and bid on some relevant keywords to target their audience. Due to the huge amount of search traffic and a wide variety of ad creations, the limits of manual optimizations from advertisers become the main bottleneck for improving the efficiency of this market. Moreover, as many emerging advertising forms and supplies are growing, it's crucial for sponsored search platform to pay more attention to the ROI metrics of ads for getting the marketing budgets of advertisers. In this paper, we present the AiAds system developed at Baidu, which use machine learning techniques to build an automated and intelligent advertising system. By designing and implementing the automated bidding strategy, the intelligent targeting and the intelligent creation models, the AiAds system can transform the manual optimizations into multiple automated tasks and optimize these tasks in advanced methods. AiAds is a brand-new architecture of sponsored search system which changes the bidding language and allocation mechanism, breaks the limit of keyword targeting with end-to-end ad retrieval framework and provides global optimization of ad creation. This system can increase the advertiser's campaign performance, the user experience and the revenue of the advertising platform simultaneously and significantly. We present the overall architecture and modeling techniques for each module of the system and share our lessons learned in solving several key challenges. Finally, online A/B test and long-term grouping experiment demonstrate the advancement and effectiveness of this system.
机译:赞助搜索有20多年的历史,已被证明是在线广告的成功商业模式。基于按单击付费定价模型和关键字定位技术,赞助系统运行在线拍卖,以确定搜索广告的分配和价格。在传统的环境中,广告商应该手动创建大量广告创作,并以某些相关的关键字出价以定位他们的受众。由于搜索流量大量和各种广告创作,广告商的手工优化的限制成为提高该市场效率的主要瓶颈。此外,由于许多新兴的广告形式和物资正在增长,这对赞助的搜索平台至关重要,以便更多地关注广告的ROI指标,以获得广告商的营销预算。在本文中,我们展示了在百度开发的AIADS系统,该系统使用机器学习技术来构建自动化和智能的广告系统。通过设计和实现自动竞标策略,智能定位和智能创建模型,AIADS系统可以将手动优化转换为多个自动化任务,并以高级方法优化这些任务。 AIAD是一个全新的赞助搜索系统体系结构,它更改了竞标语言和分配机制,突破了与端到端广告检索框架的关键字的极限,并提供了广告创建的全局优化。该系统可以同时和显着增加广告商的广告商的竞选性能,用户体验和广告平台的收入。我们为系统的每个模块提供了整体架构和建模技术,并在解决几个关键挑战方面分享我们的经验教训。最后,在线A / B测试和长期分组实验证明了该系统的进步和有效性。

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