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Real-time-ready behavioral targeting in a large-scale advertisement system

机译:大型广告系统中的实时行为定位

摘要

A “Real-Time-Ready Analyzer” combines a data stream management system (DSMS) with a map-reduce (M-R) framework to construct a streaming map-reduce framework that is suitable for real-time Behavioral Targeting (BT) (or other temporal queries). The Real-Time-Ready Analyzer allows users to write “dual-intent” temporal analysis queries for BT. These queries are succinct and easy to express, scale well on large-scale offline data, and can also work over real-time data. Further, the Real-Time-Ready Analyzer uses the aforementioned streaming map-reduce framework to provide dual-intent algorithms for end-to-end BT phases. Experiments using real data from an advertisement system show that the Real-Time-Ready Analyzer is very efficient and incurs orders-of-magnitude lower development effort than conventional systems.
机译:“实时就绪分析器”将数据流管理系统(DSMS)与地图减少(MR)框架相结合,以构建适用于实时行为目标(BT)(或其他)的流式地图减少框架。时间查询)。实时就绪分析器允许用户编写BT的“双重意图”时间分析查询。这些查询简洁明了,易于表达,可以在大规模脱机数据上很好地扩展,还可以处理实时数据。此外,实时就绪分析器使用前述的流映射减少框架来为端到端BT阶段提供双重意图算法。使用来自广告系统的真实数据进行的实验表明,实时就绪分析器非常有效,与传统系统相比,开发工作量要低几个数量级。

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