公开(公告)号：US20230245010A1

公开(公告)日：2023-08-03

申请号：US17589763

申请日：2022-01-31

申请人： salesforce.com, inc.

发明人： Sarah Joann Aerni ,  Zineb Laraki ,  Penny Tselikis ,  Till Christian Bergmann ,  Michael Weil ,  Christian Posse ,  Jason Teller ,  Alex Edelstein ,  Mehmet Ezbiderli

IPC分类号： G06Q10/06

CPC分类号： G06Q10/063112

摘要： Methods, systems, apparatuses, devices, and computer program products are described. An intelligent routing system may route a data object to a path in a process flow using a model, such as a machine-learned model. The system may receive a first data object and may route the first data object along a path of the process flow using a random routing procedure, for example, for model training. The routing may involve performing operations based on the path and the features of the first data object. The system may update one or more models based on an outcome of the operations. Following training, the system may insert a model into the process flow at a decision point between paths. The system may receive a second data object and may route the second data object to a path using the model and based on features of the second data object.

公开(公告)号：US11720825B2

公开(公告)日：2023-08-08

申请号：US16263927

申请日：2019-01-31

申请人： salesforce.com, inc.

发明人： Sarah Aerni ,  Luke Sedney ,  Kin Fai Kan ,  Till Christian Bergmann

IPC分类号： G06N20/20 ,  G06F11/34 ,  G06N5/043

CPC分类号： G06N20/20 ,  G06F11/3466 ,  G06N5/043

摘要： 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.

公开(公告)号：US20230244686A1

公开(公告)日：2023-08-03

申请号：US17589778

申请日：2022-01-31

申请人： salesforce.com, inc.

发明人： Zineb Laraki ,  Penny Tselikis ,  Till Christian Bergmann ,  Michael Weil ,  Christian Posse ,  Jason Teller ,  Alex Edelstein ,  Sarah Joann Aerni ,  Mehmet Ezbiderli

IPC分类号： G06F16/25 ,  G06F16/23 ,  G06F16/2457 ,  G06N20/00

CPC分类号： G06F16/254 ,  G06F16/23 ,  G06F16/2457 ,  G06N20/00

摘要： Methods, systems, apparatuses, devices, and computer program products are described. A system may identify, from an event log including log entries for a tenant of a multi-tenant database system, a pattern of log entries corresponding to main actions and satisfying a frequency threshold. The system may identify log entries associated with the pattern and corresponding to the main actions, detailed actions, or both. The system may retrieve data corresponding to a history field of a data object associated with the pattern and may determine at least a portion of a process flow for the data object according to the pattern and based on the log entries and the historical data. The process flow may include operations to perform using the data object. In some cases, the system may transmit, to a user device, an indication of the portion of the process flow for user review and implementation.

公开(公告)号：US20190138946A1

公开(公告)日：2019-05-09

申请号：US15884878

申请日：2018-01-31

申请人： salesforce.com, inc.

发明人： Sara Beth Asher ,  John Emery Ball ,  Vitaly Gordon ,  Till Christian Bergmann ,  Kin Fai Kan ,  Chalenge Masekera ,  Shubha Nabar ,  Nihar Dandekar ,  James Reber Lewis

IPC分类号： G06N99/00 ,  G06N5/04 ,  G06N5/02

摘要： 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.

公开(公告)号：US20200250587A1

公开(公告)日：2020-08-06

申请号：US16263927

申请日：2019-01-31

申请人： salesforce.com, inc.

发明人： Sarah Aerni ,  Luke Sedney ,  Kin Fai Kan ,  Till Christian Bergmann

IPC分类号： G06N20/20 ,  G06N5/04 ,  G06F11/34

摘要： 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.