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A sampling method based on forecasting and combinatorial optimization for high performance A/B testing
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作者 Fan LI Tiancheng ZHANG +6 位作者 Shengjia CUI Hengyu LIU Zhibin REN donglin di Xiao WANG Po ZHANG Ge YU 《Frontiers of Computer Science》 SCIE EI CSCD 2023年第6期183-185,共3页
1 Introduction A/B testing[1]is a popular statistical method for many applications,especially,widely used by Internet companies for user experience research.The sampling algorithm is an important part of A/B testing a... 1 Introduction A/B testing[1]is a popular statistical method for many applications,especially,widely used by Internet companies for user experience research.The sampling algorithm is an important part of A/B testing and has a critical impact on the performance of A/B testing.There are two challenges to achieving high performance in A/B testing.(1)The features of individuals being sampled change over time and the sampling results used for evaluation are valid only for a period of time.(2)The sampling methods in A/B testing require determining whether the two groups of samples have an identical distribution while Simple Random Sampling(SRS)has a different purpose,which only concerns whether the sample distribution is identical to the population. 展开更多
关键词 TESTING INDIVIDUAL PERFORMANCE
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