图 书 馆
基于Web的排序问题的在线参数选择Online Parameter Selection for Web-based Ranking Problems |
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| 课程网址: | http://videolectures.net/kdd2018_agarwal_online_parameter_selecti... |
| 主讲教师: | Deepak Agarwal |
| 开课单位: | 领英公司 |
| 开课时间: | 2018-11-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Web-based ranking problems involve ordering different kinds of items in a list or grid to be displayed in mediums like a website or a mobile app. In most cases, there are multiple objectives or metrics like clicks, viral actions, job applications, advertising revenue and others that we want to balance. Constructing a serving algorithm that achieves the desired tradeoff among multiple objectives is challenging, especially for more than two objectives. In addition, it is often not possible to estimate such a serving scheme using offline data alone for non-stationary systems with frequent online interventions. We consider a large-scale online application where metrics for multiple objectives are continuously available and can be controlled in a desired fashion by changing certain control parameters in the ranking model. We assume that the desired balance of metrics is known from business considerations. Our approach models the balance criteria as a composite utility function via a Gaussian process over the space of control parameters. We show that obtaining a solution can be equated to finding the maximum of the Gaussian process, practically obtainable via Bayesian optimization. However, implementing such a scheme for large-scale applications is challenging. We provide a novel framework to do so and illustrate its efficacy in the context of LinkedIn Feed. In particular, we show the effectiveness of our method by using both offline simulations as well as promising online A/B testing results. At the time of writing this paper, the method described was fully deployed on the LinkedIn Feed. |
| 关 键 词: | 基于Web的排序问题; 在线参数选择; LinkedIn Feed; 基于网络的排名问题; 不同类型的项目进行排序 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-03-23：cyh |
| 最后编审: | 2023-03-27：cyh |
| 阅读次数: | 37 |