公开(公告)号：US20160364745A1

公开(公告)日：2016-12-15

申请号：US14734515

申请日：2015-06-09

Applicant: Yahoo! Inc.

Inventor： Yan He ,  Miao Chen ,  Maria Stone

IPC: G06Q30/02

Abstract: Online experimentation has been widely used to evaluate an effect of a new feature of an online product on user engagement. One challenge is that an existence of outliers can often complicate the analysis of such experimental results. Thus, a procedure is provided herein to detect and remove outliers from experimental results. The procedure can use statistical tests based on parametric distributions of sample maximum or minimum. These tests can be performed using an inward testing procedure to identify multiple outliers. Finally, these filtered test results can be used to control delivery of a new feature of an online product.

Abstract translation: 在线实验被广泛用于评估在线产品的新功能对用户参与的影响。 一个挑战是，异常值的存在往往会使这些实验结果的分析复杂化。 因此，本文提供了一种从实验结果中检测和去除异常值的过程。 该过程可以使用基于样本最大值或最小值的参数分布的统计检验。 这些测试可以使用向内测试程序进行，以识别多个异常值。 最后，这些过滤的测试结果可用于控制在线产品的新功能的传递。