公开(公告)号：US20170098236A1

公开(公告)日：2017-04-06

申请号：US14873757

申请日：2015-10-02

Applicant: Yahoo! Inc.

Inventor： Kuang-chih Lee ,  Quan Lu ,  Giovanni Gardelli ,  Donglin Niu

IPC: G06Q30/02 ,  G06F17/30 ,  G06Q10/06

CPC classification number: G06Q30/0244 ,  G06Q10/067 ,  G06Q30/0247 ,  G06Q30/0275

Abstract: Described herein are example systems and operations for enhancing response prediction and bidding decision making. A feature recommendation controller may include a factorization machine that generates a set of combinations of contextual and advertiser features yielding high expected response rates. A bidding controller may implement a multi-arm bandit system that uses Thompson sampling to select an optimal one of the feature combinations that corresponds to a highest expected response rate. The bidding controller may compare the corresponding highest expected response rate with a threshold response rate associated with a pacing rate to determine whether to place a bid for a received ad request.

公开(公告)号：US20160180372A1

公开(公告)日：2016-06-23

申请号：US14577223

申请日：2014-12-19

Applicant: Yahoo! Inc.

Inventor： Quan LU ,  Kuang-chih Lee ,  Donglin Niu ,  Jian Xu

IPC: G06Q30/02 ,  G06N5/04 ,  G06N7/00

CPC classification number: G06Q30/0242

Abstract: A computer system implementing a method for ad realization prediction may be configured to receive a plurality of target realization factors associated with a target ad display opportunity; determine a reference realization probability score of the target ad display opportunity based on a global reference realization probability distribution associated with an ad display realization probability decision tree; using the reference realization probability score, determine an ad realization probability score of the target ad display opportunity according to a piecewise calibrated realization probability function; and return the ad realization probability score.

Abstract translation: 实现用于广告实现预测的方法的计算机系统可以被配置为接收与目标广告显示机会相关联的多个目标实现因素; 基于与广告显示实现概率决策树相关联的全局参考实现概率分布来确定目标广告显示机会的参考实现概率得分; 使用参考实现概率分数，根据分段校准的实现概率函数确定目标广告显示机会的广告实现概率分数; 并返回广告实现概率得分。