公开(公告)号：US20200057959A1

公开(公告)日：2020-02-20

申请号：US16264659

申请日：2019-01-31

Applicant: salesforce.com, inc.

Inventor： Kevin Moore ,  Leah McGuire ,  Matvey Tovbin ,  Mayukh Bhaowal ,  Shubha Nabar

IPC: G06N20/00

Abstract: Instances of data associated with hindsight bias in a training set of data for a machine learning system can be reduced. A first set of data, having a first set of fields, can be received. Data in a first field can be analyzed with respect to data in a second field corresponding to an event to be predicted. A result can be that the data in the first field is associated with hindsight bias. A second set of data, having a second set of fields, can be produced. The second set of fields can exclude the first field. One or more features associated with the second set of data can be generated. A third set of data, having the second set of fields and fields that correspond to the one or more features, can be produced. The training set of data can be produced using the third set of data.

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.

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.

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

IPC: G06K9/62 ,  G06N5/04 ,  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.