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公开(公告)号:US20210027338A1
公开(公告)日:2021-01-28
申请号:US16520556
申请日:2019-07-24
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:US20200301966A1
公开(公告)日:2020-09-24
申请号:US16355996
申请日:2019-03-18
Applicant: salesforce.com, inc.
Inventor: Nathan Irace Burke , Kexin Xie , Xingyu Wang , Wanderley Liu , David Yourdon
IPC: G06F16/906 , G06K9/62 , G06F17/18
Abstract: A data processing server may receive a set of data objects for frequent pattern (FP) analysis. The set of data objects may be analyzed using an attribute diversity technique. For the set of data attributes of the set of data objects, the server may arrange the attributes in one or more dimensions. The server may initialize a set of centroids on data points and identify mean values of nearby data points. Based on an iteration of the mean value calculation, the server may identify a set of attributes corresponding to final mean values as being groups of similarly frequent attributes. These groups of similarly frequent attributes may be analyzed using an FP analysis procedure to identify frequent patterns of data attributes.
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公开(公告)号:US20200137008A1
公开(公告)日:2020-04-30
申请号:US16177271
申请日:2018-10-31
Applicant: salesforce.com, Inc.
Inventor: Zhao Jin , Shrestha Basu Mallick , Yacov Salomon , Kexin Xie , Sheng Loong Su , Todd Swardenski , Trent Albright , Armita Peymandoust , Michael Jones , Brian Brechbuhl , David Yourdon
Abstract: A database server may receive or monitor user engagement metadata corresponding to a plurality of communication messages transmitted to the users. The database server analyzes the metadata to determine optimal transmission frequencies for digital communication messages based on engagement rates received in the user engagement metadata.
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