公开(公告)号：US11544465B2

公开(公告)日：2023-01-03

申请号：US17211162

申请日：2021-03-24

Applicant: salesforce.com, inc.

Inventor： Michael Machado ,  John Ball ,  Thomas Archie Cook, Jr. ,  Shashank Harinath ,  Roojuta Lalani ,  Zineb Laraki ,  Qingqing Liu ,  Mike Rosenbaum ,  Karl Ryszard Skucha ,  Jean-Marc Soumet ,  Manju Vijayakumar

IPC: G06F40/295 ,  G06F16/332 ,  G06F40/30 ,  G10L15/18 ,  G10L15/22 ,  G10L15/30

Abstract: Approaches to using unstructured input to update heterogeneous data stores include receiving unstructured text input, receiving a template for interpreting the unstructured text input, identifying, using an entity classifier, entities in the unstructured text input, identifying one or more potential parent entities from the identified entities based on the template, receiving a selection of a parent entity from the one or more potential parent entities, identifying one or more potential child entities from the identified entities based on the template and the selected parent entity, receiving a selection of a child entity from the one or more potential child entities, identifying an action item in the unstructured text input based on the identified entities and the template, determining, using an intent classifier, an intent of the action item, and updating a data store based on the determined intent, the identified entities, and the selected child entity.

公开(公告)号：US20210141865A1

公开(公告)日：2021-05-13

申请号：US16680323

申请日：2019-11-11

Applicant: salesforce.com, inc.

Inventor： Michael Machado ,  James Douglas Harrison ,  Caiming Xiong ,  Xinyi Yang ,  Thomas Archie Cook ,  Roojuta Lalani ,  Jean-Marc Soumet ,  Karl Ryszard Skucha ,  Juan Manuel Rodriguez ,  Manju Vijayakumar ,  Vishal Motwani ,  Tian Xie ,  Bryan McCann ,  Nitish Shirish Keskar ,  Armen Abrahamyan ,  Zhihao Zou ,  Chitra Gulabrani ,  Minal Khodani ,  Adarsha Badarinath ,  Rohiniben Thakar ,  Srikanth Kollu ,  Kevin Schoen ,  Qiong Liu ,  Amit Hetawal ,  Kevin Zhang ,  Kevin Zhang ,  Victor Brouk ,  Johnson Liu ,  Rafael Amsili

IPC: G06F17/27 ,  G06N3/08 ,  G06N3/04 ,  H04L12/58

Abstract: A multi-tenant system performs custom configuration of a tenant-specific chatbot to process and act upon natural language requests. The multi-tenant system configures the tenant-specific chatbots without requiring tenant-specific training. The multi-tenant system providing a user interface for configuring a tenant-specific set of permitted actions. The multi-tenant system determines a set of example phrases for each of the selected permitted actions. The multi-tenant system receives a natural language request from a user and identifies the action that the user wants to perform. The multi-tenant system uses a neural network to compare the natural language request with example phrases to identify an example phrase that matches the natural language request. The multi-tenant system performs the action corresponding to the matching example phrase.

公开(公告)号：US11769013B2

公开(公告)日：2023-09-26

申请号：US16680323

申请日：2019-11-11

Applicant: salesforce.com, inc.

Inventor： Michael Machado ,  James Douglas Harrison ,  Caiming Xiong ,  Xinyi Yang ,  Thomas Archie Cook ,  Roojuta Lalani ,  Jean-Marc Soumet ,  Karl Ryszard Skucha ,  Juan Rodriguez ,  Manju Vijayakumar ,  Vishal Motwani ,  Tian Xie ,  Bryan McCann ,  Nitish Shirish Keskar ,  Zhihao Zou ,  Chitra Gulabrani ,  Minal Khodani ,  Adarsha Badarinath ,  Rohiniben Thakar ,  Srikanth Kollu ,  Kevin Schoen ,  Qiong Liu ,  Amit Hetawal ,  Kevin Zhang ,  Kevin Zhang ,  Johnson Liu ,  Rafael Amsili

IPC: G10L15/16 ,  G06F40/30 ,  G06N3/08 ,  H04L51/02 ,  G06N3/04 ,  G06F40/295

CPC classification number: G06F40/30 ,  G06F40/295 ,  G06N3/04 ,  G06N3/08 ,  H04L51/02

Abstract: A multi-tenant system performs custom configuration of a tenant-specific chatbot to process and act upon natural language requests. The multi-tenant system configures the tenant-specific chatbots without requiring tenant-specific training. The multi-tenant system providing a user interface for configuring a tenant-specific set of permitted actions. The multi-tenant system determines a set of example phrases for each of the selected permitted actions. The multi-tenant system receives a natural language request from a user and identifies the action that the user wants to perform. The multi-tenant system uses a neural network to compare the natural language request with example phrases to identify an example phrase that matches the natural language request. The multi-tenant system performs the action corresponding to the matching example phrase.

公开(公告)号：US10970486B2

公开(公告)日：2021-04-06

申请号：US16134956

申请日：2018-09-18

Applicant: salesforce.com, inc.

Inventor： Michael Machado ,  John Ball ,  Thomas Archie Cook, Jr. ,  Shashank Harinath ,  Roojuta Lalani ,  Zineb Laraki ,  Qingqing Liu ,  Mike Rosenbaum ,  Karl Ryszard Skucha ,  Jean-Marc Soumet ,  Manju Vijayakumar

IPC: G06F40/295 ,  G06F16/332 ,  G06F40/30 ,  G10L15/18 ,  G10L15/22 ,  G10L15/30

Abstract: Approaches to using unstructured input to update heterogeneous data stores include receiving unstructured text input, receiving a template for interpreting the unstructured text input, identifying, using an entity classifier, entities in the unstructured text input, identifying one or more potential parent entities from the identified entities based on the template, receiving a selection of a parent entity from the one or more potential parent entities, identifying one or more potential child entities from the identified entities based on the template and the selected parent entity, receiving a selection of a child entity from the one or more potential child entities, identifying an action item in the unstructured text input based on the identified entities and the template, determining, using an intent classifier, an intent of the action item, and updating a data store based on the determined intent, the identified entities, and the selected child entity.