图 书 馆
电子商务定价系统的异常检测Anomaly Detection for an E-commerce Pricing System |
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| 课程网址: | http://videolectures.net/kdd2019_ramakrishnan_shaabani_li/ |
| 主讲教师: | Jagdish Ramakrishnan |
| 开课单位: | 沃尔玛实验室 |
| 开课时间: | 2020-03-02 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Online retailers execute a very large number of price updates when compared to brick-and-mortar stores. Even a few mis-priced items can have a significant business impact and result in a loss of customer trust. Early detection of anomalies in an automated real-time fashion is an important part of such a pricing system. In this paper, we describe unsupervised and supervised anomaly detection approaches we developed and deployed for a large-scale online pricing system at Walmart. Our system detects anomalies both in batch and real-time streaming settings, and the items flagged are reviewed and actioned based on priority and business impact. We found that having the right architecture design was critical to facilitate model performance at scale, and business impact and speed were important factors influencing model selection, parameter choice, and prioritization in a production environment for a large-scale system. We conducted analyses on the performance of various approaches on a test set using real-world retail data and fully deployed our approach into production. We found that our approach was able to detect the most important anomalies with high precision. |
| 关 键 词: | 电子商务定价系统; 大数据科学; 异常检测 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2022-09-19：cyh |
| 最后编审: | 2022-09-19：cyh |
| 阅读次数: | 48 |