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公开(公告)号：US20220244988A1
公开(公告)日：2022-08-04
申请号：US17163386
申请日：2021-01-30
Applicant: salesforce.com, inc.
Inventor： Yuxi Zhang , Kexin Xie
Abstract: Systems, devices, and techniques are disclosed for data shards for distributed processing. Data sets of data for users may be received. The data sets may belong to separate groups. User identifiers in the data sets may be hashed to generate hashed identifiers for the data sets. The user identifiers in the data sets may be replaced with the hashed identifiers. The data sets may be split to generate shards. The data sets may be split into the same number of shards. Merged shards may be generated by merging the shards using a separate running process for each of the merged shards. The merged shards may be generated using shards from more than one of the two or more data sets. An operation may be performed on all of the merged shards.
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公开(公告)号：US20220198529A1
公开(公告)日：2022-06-23
申请号：US17563874
申请日：2021-12-28
Applicant: salesforce.com, inc.
Inventor： Yuxi Zhang , Kexin Xie , Shrestha Basu Mallick , Darrell Grissen
IPC: G06Q30/02
Abstract: A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior pattern can be identified based on two or more interaction points stored in the user data. An intent of the user based on the behavior pattern can be identified. The intent can be based on a previous behavior pattern of another user. Several probabilities that the user will meet one or more objectives can be determined based on the intent. The probabilities can be scored using and used to assign a policy to the first user. A next action can be recommended based on the policy and executed with respect to the user. The outcome of the recommended next action can be stored to the user data.
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公开(公告)号：US20210287246A1
公开(公告)日：2021-09-16
申请号：US16818016
申请日：2020-03-13
Applicant: salesforce.com, inc.
Inventor： Yuxi Zhang , Kexin Xie
IPC: G06Q30/02
Abstract: Systems, device and techniques are disclosed for asynchronous remote call with undo data structures. A selection of a data point of a time series may be received. The data point may represent a measurement of an overall target metric for events at a point in time. A graph for the data point may be displayed on a display device. The display of the graph for the data point may include nodes for the events displayed with sizes based on an influence scores for the events, and an edge between each of the nodes and a hidden node, with a width that may represent an adjusted change in a measurement of a target metric for the event corresponding to the node, and a color of the edge may represent whether the adjusted change in the measurement of the target metric for the event is positive or negative.
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公开(公告)号：US20200322307A1
公开(公告)日：2020-10-08
申请号：US16506773
申请日：2019-07-09
Applicant: salesforce.com, inc.
Inventor： Yuxi Zhang , Kexin Xie , Sheng Loong Su , Shrestha Basu Mallick
Abstract: A cloud platform supports a digital communication system that identifies recommended communication frequencies based on past communication data. The cloud platform may support blending of weights applied to different engagement rates. Based on the weights, the system identifies recommended frequency ranges to maximize engagement rates, including the blended engagement rate using a redistribution simulation process.
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公开(公告)号：US12236264B2
公开(公告)日：2025-02-25
申请号：US17163386
申请日：2021-01-30
Applicant: salesforce.com, inc.
Inventor： Yuxi Zhang , Kexin Xie
Abstract: Systems, devices, and techniques are disclosed for data shards for distributed processing. Data sets of data for users may be received. The data sets may belong to separate groups. User identifiers in the data sets may be hashed to generate hashed identifiers for the data sets. The user identifiers in the data sets may be replaced with the hashed identifiers. The data sets may be split to generate shards. The data sets may be split into the same number of shards. Merged shards may be generated by merging the shards using a separate running process for each of the merged shards. The merged shards may be generated using shards from more than one of the two or more data sets. An operation may be performed on all of the merged shards.
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Patent Agency Ranking
公开(公告)号：US20220207407A1
公开(公告)日：2022-06-30
申请号：US17134430
申请日：2020-12-27
Applicant: salesforce.com, inc.
Inventor： Yuxi Zhang , Kexin Xie
Abstract: Systems, devices, and techniques are disclosed for localization of machine learning models trained with global data. Data sets of event data for users may be received. The data sets may belong to separate groups. The data sets of event data may be combined to generate a global data set. A matrix factorization model may be trained using the global data set to generate a globally trained matrix factorization model. A localization group data set may be generated including event data from the global data set for users from a first of the groups. The globally trained matrix factorization model may be trained with the localization group data set to generate a localized matrix factorization model for the first of the groups.
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公开(公告)号：US11900424B2
公开(公告)日：2024-02-13
申请号：US17563874
申请日：2021-12-28
Applicant: salesforce.com, inc.
Inventor： Yuxi Zhang , Kexin Xie , Shrestha Basu Mallick , Darrell Grissen
IPC: G06Q30/02 , G06Q30/0251 , G06Q30/0201
CPC classification number: G06Q30/0281 , G06Q30/0201 , G06Q30/0271
Abstract: A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior pattern can be identified based on two or more interaction points stored in the user data. An intent of the user based on the behavior pattern can be identified. The intent can be based on a previous behavior pattern of another user. Several probabilities that the user will meet one or more objectives can be determined based on the intent. The probabilities can be scored using and used to assign a policy to the first user. A next action can be recommended based on the policy and executed with respect to the user. The outcome of the recommended next action can be stored to the user data.
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公开(公告)号：US20230004860A1
公开(公告)日：2023-01-05
申请号：US17366249
申请日：2021-07-02
Applicant: salesforce.com, inc.
Inventor： Donglin Hu , Yuxi Zhang , Kexin Xie
Abstract: Methods, computer readable media, and devices for determining a hyperparameter for influencing non-local samples in machine learning are disclosed. One method may include identifying a set of local samples associated with a first entity, identifying a set of non-local samples comprising samples associated with a plurality of entities other than the first entity, assigning a local sample weight to one or more samples of the set of local samples, determining a range of non-local sample weights, determining a range of hyperparameters based on the range of non-local sample weights, determining an optimized hyperparameter based on the range of hyperparameters, assigning an optimized non-local sample weight to one or more samples of the set of non-local samples, and generating a prediction using machine learning.
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公开(公告)号：US11431663B2
公开(公告)日：2022-08-30
申请号：US16662718
申请日：2019-10-24
Applicant: salesforce.com, inc.
Inventor： Yuxi Zhang , Kexin Xie
Abstract: Disclosed embodiments are related to send time optimization technologies for sending messages to users. The send time optimization technologies provide personalized recommendations for sending messages to individual subscribers taking into account the delay and/or lag between the send time and the time when a subscriber engages with a sent message. A machine learning (ML) approach is used to predict the optimal send time to send messages to individual subscribers for improving message engagement. The personalized recommendations are based on unique characteristics of each user's engagement preferences and patterns, and deals with historical feedback that is generally incomplete and skewed towards a small set of send hours. The ML approach automatically discovers hidden factors underneath message and send time engagements. The ML model may be a two-layer non-linear matrix factorization model. Other embodiments may be described and/or claimed.
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公开(公告)号：US11425084B2
公开(公告)日：2022-08-23
申请号：US16506773
申请日：2019-07-09
Applicant: salesforce.com, inc.
Inventor： Yuxi Zhang , Kexin Xie , Sheng Loong Su , Shrestha Basu Mallick
IPC: G06Q30/02 , G06Q10/06 , H04L51/234 , H04L51/52 , H04L51/56
Abstract: A cloud platform supports a digital communication system that identifies recommended communication frequencies based on past communication data. The cloud platform may support blending of weights applied to different engagement rates. Based on the weights, the system identifies recommended frequency ranges to maximize engagement rates, including the blended engagement rate using a redistribution simulation process.
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