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    ACTIONABLE KPI-DRIVEN SEGMENTATION
    1.
    发明申请
    ACTIONABLE KPI-DRIVEN SEGMENTATION 审中-公开

    公开(公告)号：US20200151746A1

    公开(公告)日：2020-05-14

    申请号：US16191289

    申请日：2018-11-14

    Applicant: ADOBE INC.

    Inventor： Xiang Wu ,  Zhenyu Yan ,  Yi-Hong Kuo ,  Wuyang Dai ,  Polina Bartik ,  Abhishek Pani

    IPC: G06Q30/02 ,  G06Q10/06 ,  G06F17/16

    Abstract: An improved analytics system generates actionable KPI-based customer segments. The analytics system determines predicted outcomes for a key performance indicator (KPI) of interest and a contribution value for each variable indicating an extent to which each variable contributes to predicted outcomes. Topics are generated by applying a topic model to the contribution values for the variables. Each topic comprises a group of variables with a contribution level for each variable that indicates the importance of each variable to the topic. User segments are generated by assigning each user to a topic based on attribution levels output by the topic model.

    UTILIZING A BAYESIAN APPROACH AND MULTI-ARMED BANDIT ALGORITHMS TO IMPROVE DISTRIBUTION TIMING OF ELECTRONIC COMMUNICATIONS
    4.
    发明申请
    UTILIZING A BAYESIAN APPROACH AND MULTI-ARMED BANDIT ALGORITHMS TO IMPROVE DISTRIBUTION TIMING OF ELECTRONIC COMMUNICATIONS 审中-公开

    公开(公告)号：US20200311487A1

    公开(公告)日：2020-10-01

    申请号：US16371460

    申请日：2019-04-01

    Applicant: Adobe Inc.

    Inventor： Jun He ,  Zhenyu Yan ,  Yi-Hong Kuo ,  Wuyang Dai ,  Shiyuan Gu ,  Abhishek Pani

    IPC: G06K9/62 ,  G06F17/27 ,  G06N7/00

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for determining send times to provide electronic communications based on predicted response rates by utilizing a Bayesian approach and multi-armed bandit algorithms. For example, the disclosed systems can generate predicted response rates by training and utilizing one or more response rate prediction models to generate a weighted combination of user-specific response information and population-specific response information. The disclosed systems can further utilize a Bayes upper-confidence-bound send time model to determine send times that are more likely to elicit user responses based on the predicted response rates and further based on exploration and exploitation considerations. In addition, the disclosed systems can update the response rate prediction models and/or the Bayes upper-confidence-bound send time model based on providing additional electronic communications and receiving additional responses to modify model weights.

    Survival Analysis Based Classification Systems for Predicting User Actions
    5.
    发明申请
    Survival Analysis Based Classification Systems for Predicting User Actions 审中-公开

    公开(公告)号：US20200065713A1

    公开(公告)日：2020-02-27

    申请号：US16112546

    申请日：2018-08-24

    Applicant: Adobe Inc.

    Inventor： Xiang Wu ,  Zhenyu Yan ,  Yi-Hong Kuo ,  Wuyang Dai ,  Julia Viladomat Comerma ,  Abhishek Pani

    IPC: G06N99/00

    Abstract: Techniques and systems are described that employ survival analysis and classification to predict occurrence of future events by a digital analytics system. Survival analysis involves modeling time to event data. Survival analysis is used by digital analytics systems to analyze an expected duration of time until an event happens. In the techniques described herein, survival analysis is employed as part of a classification technique by a digital analytics system. In one example, a digital analytics system generates training data from a dataset in accordance with a survival analysis technique such that, after generated, the training data is usable to train a classification model.

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