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公开(公告)号：US20230110057A1
公开(公告)日：2023-04-13
申请号：US17496615
申请日：2021-10-07
Applicant: salesforce.com, inc.
Inventor： Kin Fai Kan , Chaney Lin , Mayukh Bhaowal , Shubha Nabar , Seiji J. Yamamoto
IPC: G06F16/2457 , G06N20/00 , G06F16/25 , G06K9/62
Abstract: A method for generating a model for recommendations from an item data set for a target data set includes embedding a set of targets from the target data set in a shared coordinate space using a first embedding function, embedding a first set of items from the item data set in the shared coordinate space using a second embedding function, selecting at least one target from the set of targets, and identifying a second set of items from the first set of items that are proximate to the at least one target as candidates from the recommendations.
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Patent Agency Ranking
公开(公告)号：US11720825B2
公开(公告)日：2023-08-08
申请号：US16263927
申请日：2019-01-31
Applicant: salesforce.com, inc.
Inventor： Sarah Aerni , Luke Sedney , Kin Fai Kan , Till Christian Bergmann
CPC classification number: G06N20/20 , G06F11/3466 , G06N5/043
Abstract: The system and methods of the disclosed subject matter provide an experimentation framework to allow a user to perform machine learning experiments on tenant data within a multi-tenant database system. The system may provide an experimental interface to allow modification of machine learning algorithms, machine learning parameters, and tenant data fields. The user may be prohibited from viewing any of the tenant data or may be permitted to view only a portion of the tenant data. Upon generating an experimental model using the experimental interface, the user may view results comparing the performance of the experimental model with a current production model.
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公开(公告)号：US20190138946A1
公开(公告)日：2019-05-09
申请号：US15884878
申请日：2018-01-31
Applicant: salesforce.com, inc.
Inventor： Sara Beth Asher , John Emery Ball , Vitaly Gordon , Till Christian Bergmann , Kin Fai Kan , Chalenge Masekera , Shubha Nabar , Nihar Dandekar , James Reber Lewis
Abstract: A system may automatically generate a predictive machine learning model by automatically performing various processes based on an analysis of the data as well as metadata associated with the data. The system may accept a selection of data and a prediction field from the data. The system may automatically generate a set of features based on the data and may automatically remove certain features that cause inaccuracies in the model. The system may balance the data based on a representation rate of certain outcomes. The system may train and select a model based on several candidate models. The system may then perform the predictions based on the selected model and send an indication of the predictions to a user.
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公开(公告)号：US20200250587A1
公开(公告)日：2020-08-06
申请号：US16263927
申请日：2019-01-31
Applicant: salesforce.com, inc.
Inventor： Sarah Aerni , Luke Sedney , Kin Fai Kan , Till Christian Bergmann
Abstract: The system and methods of the disclosed subject matter provide an experimentation framework to allow a user to perform machine learning experiments on tenant data within a multi-tenant database system. The system may provide an experimental interface to allow modification of machine learning algorithms, machine learning parameters, and tenant data fields. The user may be prohibited from viewing any of the tenant data or may be permitted to view only a portion of the tenant data. Upon generating an experimental model using the experimental interface, the user may view results comparing the performance of the experimental model with a current production model.
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公开(公告)号：US11669767B2
公开(公告)日：2023-06-06
申请号：US16542228
申请日：2019-08-15
Applicant: salesforce.com, inc.
Inventor： Mayukh Bhaowal , Leah McGuire , Kin Fai Kan , Christopher Rupley , Xiaodan Sun , Michael Weil , Subha Nabar
IPC: G06Q10/0637 , G06F18/21 , G06N20/00 , G06N5/045 , G06F18/214
CPC classification number: G06F18/2185 , G06F18/2148 , G06N5/045 , G06N20/00
Abstract: A set of data for training a machine learning system can be modified to improve its performance. An item of information can be transmitted. A message can be transmitted that includes an explanation of a determination, by the machine learning system, to transmit the item of information from among a plurality of items of information. A first set of data can have been used to train the machine learning system. A signal can be received that includes an indication of a usefulness of the message, to a user of a user device, in making a decision to perform an action based on a knowledge associated with the item of information. The first set of data can be modified, in response to a receipt of the signal, to produce a second set of data. The machine learning system can be caused to be trained using the second set of data.
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公开(公告)号：US20210049419A1
公开(公告)日：2021-02-18
申请号：US16542228
申请日：2019-08-15
Applicant: salesforce.com, inc.
Inventor： Mayukh Bhaowal , Leah McGuire , Kin Fai Kan , Christopher Rupley , Xiaodan Sun , Michael Weil , Subha Nabar
Abstract: A set of data for training a machine learning system can be modified to improve its performance. An item of information can be transmitted. A message can be transmitted that includes an explanation of a determination, by the machine learning system, to transmit the item of information from among a plurality of items of information. A first set of data can have been used to train the machine learning system. A signal can be received that includes an indication of a usefulness of the message, to a user of a user device, in making a decision to perform an action based on a knowledge associated with the item of information. The first set of data can be modified, in response to a receipt of the signal, to produce a second set of data. The machine learning system can be caused to be trained using the second set of data.
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