公开(公告)号：US20240323156A1

公开(公告)日：2024-09-26

申请号：US18680804

申请日：2024-05-31

Applicant: Adobe Inc.

Inventor： Lijun Yu ,  Wuyang Dai ,  Jun He ,  Hsiang-Yu Yang ,  Zhenyu Yan

IPC: H04L51/222 ,  G06F18/10 ,  G06F18/21 ,  G06F18/214 ,  G06F18/2413 ,  G06N20/00

CPC classification number: H04L51/222 ,  G06F18/10 ,  G06F18/214 ,  G06F18/217 ,  G06F18/24147 ,  G06N20/00

Abstract: Methods and systems are provided for facilitating time zone prediction using electronic communication data. Electronic message data associated with a message recipient of electronic communications is obtained. The electronic message data includes message delivery data associated with an electronic message and message response data associated with a response, by the message recipient, to a received electronic message. Using a machine learning model and based on the message delivery data and the message response data, a time-zone score is determined for a time zone. Such a time-zone score can indicate a probability the time zone corresponds with the message recipient. Based on the time-zone score, the time zone is identified as corresponding with the message recipient.

公开(公告)号：US11961109B2

公开(公告)日：2024-04-16

申请号：US16742386

申请日：2020-01-14

Applicant: ADOBE INC.

Inventor： Lei Zhang ,  Jun He ,  Tingting Xu ,  Jalaj Bhandari ,  Wuyang Dai ,  Zhenyu Yan

IPC: G06Q30/00 ,  G06F18/20 ,  G06N3/08 ,  G06N20/00 ,  G06Q10/107 ,  G06Q30/0207

CPC classification number: G06Q30/0239 ,  G06F18/295 ,  G06N3/08 ,  G06N20/00 ,  G06Q10/107

Abstract: Systems and methods for customer journey optimization in email marketing are described. The systems and methods may identify a plurality of messages for a first time period, wherein the plurality of messages are categorized according to a plurality of messages types, identify user information for a customer, wherein the user information includes user interaction data, determine a message type from the plurality of message types for the first time period based on the user information, wherein the message type is determined using a decision making model comprising a deep Q-learning neural network, select a message from the plurality of messages based on the determined message type, and transmit the message to the customer during the first time period based on the selection.

公开(公告)号：US11645542B2

公开(公告)日：2023-05-09

申请号：US16384558

申请日：2019-04-15

Applicant: Adobe Inc.

Inventor： Lei Zhang ,  Jun He ,  Zhenyu Yan ,  Wuyang Dai ,  Abhishek Pani

IPC: G06F17/18 ,  G06N3/086 ,  G06N3/10 ,  G06Q30/02 ,  G06F8/38

CPC classification number: G06N3/086 ,  G06F17/18 ,  G06N3/10

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a target distribution schedule for providing electronic communications based on predicted behavior rates by utilizing a genetic algorithm and one or more objective functions. For example, the disclosed systems can generate predicted behavior rates by training and utilizing one or more behavior prediction models. Based on the predicted behavior rates, the disclosed systems can further utilize a genetic algorithm to apply objective functions to generate one or more candidate distribution schedules. In accordance with the genetic algorithm, the disclosed systems can select a target distribution schedule for a particular user/client device. The disclosed systems can thus provide one or more electronic communications to individual users based on respective target distribution schedules.

公开(公告)号：US20230129808A1

公开(公告)日：2023-04-27

申请号：US17509885

申请日：2021-10-25

Applicant: ADOBE INC.

Inventor： Lijun Yu ,  Wuyang Dai ,  Jun He ,  Hsiang-Yu Yang ,  Zhenyu Yan

IPC: H04L12/58 ,  G06K9/62 ,  G06N20/00

Abstract: Methods and systems are provided for facilitating time zone prediction using electronic communication data. Electronic message data associated with a message recipient of electronic communications is obtained. The electronic message data includes message delivery data associated with an electronic message and message response data associated with a response, by the message recipient, to a received electronic message. Using a machine learning model and based on the message delivery data and the message response data, a time-zone score is determined for a time zone. Such a time-zone score can indicate a probability the time zone corresponds with the message recipient. Based on the time-zone score, the time zone is identified as corresponding with the message recipient.

公开(公告)号：US20230005023A1

公开(公告)日：2023-01-05

申请号：US17366910

申请日：2021-07-02

Applicant: ADOBE INC.

Inventor： Lei Zhang ,  Lijun Yu ,  Jun He ,  Zhenyu Yan ,  Wuyang Dai

IPC: G06Q30/02

Abstract: Methods and systems are provided for improved electronic communication campaign technologies, which can automatically balance objectives or goals of an electronic communication campaign against an overall opt-out rate for the electronic communication campaign. An electronic communications frequency optimizer can generate individual contact frequencies for individual email recipients. Embodiments can avoid unnecessary or counterproductive communications while achieving overall campaign goals, and can use processes to improve the efficiency of systems. In some cases, embodiments cluster communication recipients into different groups based on their past actions, then optimizes the communication contact frequency on different groups, to avoid performing optimization directly on millions of recipients. Some embodiments automatically self-update, for example with recipients' recent responses, to generate and/or implement campaign communication schedules on an individual level.

公开(公告)号：US11514515B2

公开(公告)日：2022-11-29

申请号：US16037700

申请日：2018-07-17

Applicant: Adobe Inc.

Inventor： Maoqi Xu ,  Zhenyu Yan ,  Jin Xu ,  Abhishek Pani

IPC: G06Q30/00 ,  G06Q40/02 ,  G06Q30/02 ,  G06N20/00 ,  G05B19/418 ,  G06N5/04

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for using reject inference to generate synthetic data for modifying lead scoring models. For example, the disclosed system identifies an original dataset corresponding to an output of a lead scoring model that generates scores for a plurality of prospects to indicate a likelihood of success of prospects of the plurality of prospects. In one or more embodiments, the disclosed system selects a reject inference model by performing simulations on historical prospect data associated with the original dataset. Additionally, the disclosed system uses the selected reject inference model to generate an imputed dataset by generating synthetic outcome data representing simulated outcomes of rejected prospects in the original dataset. The disclosed system then uses the imputed dataset to modify the lead scoring model by modifying at least one parameter of the lead scoring model using the synthetic outcome data.

公开(公告)号：US11080764B2

公开(公告)日：2021-08-03

申请号：US15458484

申请日：2017-03-14

Applicant: ADOBE INC.

Inventor： Chen Dong ,  Zhenyu Yan ,  Pinak Panigrahi ,  Xiang Wu ,  Abhishek Pani

IPC: G06Q30/02 ,  G06N7/00 ,  G06F16/951 ,  G06F16/245 ,  G06Q30/08

Abstract: A bid management system generates estimated performance metrics at the bid unit level to facilitate bid optimization. The bid management system includes a hierarchical feature selection and prediction approach. Feature selection is performed by aggregating historical performance metrics to a higher hierarchical level and testing features for statistical significance. Features for which a significance level satisfies a significance threshold are selected for prediction analysis. The prediction analysis uses a statistical model based on selected features to generate estimated performance metrics at the bid unit level. In some implementations, the prediction analysis uses a hierarchical Bayesian smoothing method in which estimated performance metrics are calculated at the bid unit level using a posterior probability distribution derived from a prior probability distribution determined based on aggregated performance metrics and a likelihood function that takes into account historical performance metrics from the bid unit level based on the selected features.

公开(公告)号：US10956930B2

公开(公告)日：2021-03-23

申请号：US16034232

申请日：2018-07-12

Applicant: Adobe Inc.

Inventor： Yuan Yuan ,  Zhenyu Yan ,  Yiwen Sun ,  Xiaojing Dong ,  Chen Dong ,  Abhishek Pani

IPC: G06Q30/02 ,  G06N7/00 ,  G06N20/00 ,  H04L29/08

Abstract: Dynamic Hierarchical Empirical Bayes techniques and systems are described that are implemented to control output of digital content. In one example, a system identifies splitting variables included in data. An amount of loss is then determined for each of the identified splitting variables by the system using a loss function. Based on the determined amounts of loss, the system selects at least one splitting variable from the plurality of splitting variables that are to be used to partition data in a respective node, e.g., a parent node to form a plurality of child nodes. The system, for instance, may select the splitting variable that minimizes the cost, i.e., has the lowest amount of cost. The selected splitting variable is then employed by the system to generate at least one hierarchical level of the hierarchical structure of the statistical model by partitioning data from the parent node into respective child nodes.

公开(公告)号：US10748178B2

公开(公告)日：2020-08-18

申请号：US14874298

申请日：2015-10-02

Applicant: ADOBE INC.

Inventor： Zhenyu Yan ,  Xiang Wu ,  Chen Dong ,  Abhishek Pani

IPC: G06Q30/00 ,  G06Q30/02

Abstract: In various implementations, analytics data is received that indicates performance of bid targets for historical bids made in one or more content delivery auctions. Baseline prediction models are maintained for the bid targets. The baseline prediction models use the analytics data to predict performance of the bid targets in one or more future instances of at least one content delivery auction. A presentation context factor model is maintained that provides an adjustment factor that quantifies a contribution of a subset of a plurality of presentation context factors associated with the bid targets to performance of the bid targets based on predicted values from the baseline prediction models. A contextual predicted value is computed using the adjustment factor for the subset of the plurality of presentation context factors. A performance prediction is transmitted to a user device and is based on at least the contextual predicted value.

公开(公告)号：US20200027102A1

公开(公告)日：2020-01-23

申请号：US16042770

申请日：2018-07-23

Applicant: Adobe Inc.

Inventor： Jin Xu ,  Zhenyu Yan ,  Wenqing Yang ,  Tianyu Wang ,  Abhishek Pani

IPC: G06Q30/02

Abstract: Quantitative rating systems and techniques are described that prioritize customers by propensity to buy and buy size to generate customer ratings. In one example, a propensity model is used to determine a likelihood of a potential customer to purchase a product, and a projected timeframe buy size for the potential customer is determined. An expected value for the potential customer is generated by combining the likelihood of the potential customer to purchase the product and the projected timeframe buy size. In another example, a ratio model of annualized recurring revenue (ARR) is used to determine a timeframe buy size for an existing customer in consecutive time frames. An upsell opportunity for the existing customer is determined based on the timeframe buy size less an ARR for a current time frame for the existing customer. A rating of the potential or existing customer is output in a user interface.