Salesforce Com, Inc.

Salesforce, Inc.

Thomas Archie Cook, Jr

Qingqing Liu

Kamyar Seradjfar

Roojuta Lalani

Jean-Marc Soumet

Manju Vijayakumar

John Christopher Houston

Christopher Douglas Seymour

Mohamad Arabo

Jody Elizabeth Bleyle

Jean Elie Bovet

Jason Schroeder

Shashank Harinath

Karl Ryszard Skucha

Michael Machado

Mike Rosenbaum

Arthur Albert Louie

John Ball

Ethan Treber

Zineb Laraki

Kevin Zhang

Caiming Xiong

Bryan McCann

Nitish Shirish Keskar

Tian Xie

Xinyi Yang

Thomas Keeney

Johnson Liu

Nick Hansen

Juan Rodriguez

James Douglas Harrison

Vivek Chauhan

Vishal Motwani

Zhihao Zou

Minal Khodani

Adarsha Badarinath

Kevin Schoen

Chitra Gulabrani

Srikanth Kollu

Rohiniben Thakar

Amit Hetawal

Qiong Liu

Rafael Amsili

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.

Machine learning based tenant-specific chatbots for performing actions in a multi-tenant system

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.

Using unstructured input to update heterogeneous data stores

Systems, methods, and computer-readable media for lazy tracking mechanisms for web caching systems are provided. The lazy tracking mechanism may track and perform asynchronous (async) computation of dirty records for client-side caching mechanisms. The async computation of dirty records may include tracking or accounting for invalidated records relevant to a particular client or user system. Invalidation messages may be sent to client/user systems in response to receipt of a request for updated records, or in response to a request for a particular item. Other embodiments may be described and/or claimed.

Lazy tracking of user system web cache

In accordance with embodiments, there are provided mechanisms and methods for facilitating management of user queries and dynamic filtration of responses based on group filters in an on-demand services environment in a multi-tenant environment according to one embodiment. In one embodiment and by way of example, a method includes receiving, at a first computing device, a query via an application programming interface ('API') of a software application at a second computing device, where the query includes one or more filter parameters including a size filter parameter. The method may further include evaluating the query based on the one or more filter parameters including the size filter parameter, selecting a first response based on the size filter parameter, and communicating the first response to be viewed via the API at the second computing device.

Facilitating management of user queries and dynamic filtration of responses based on group filters in an on-demand services environment

The technology disclosed includes a method for initiating a web service through an action item within a post in a social media network. A request is received from a user for a post to a social network. The request includes a definition for an action-link-group, which comprises one or more action links. The post is created to include the action-link-group and is then uploaded to the network. Upon receiving a selection of an action link within the action-link-group, an action item associated with the action link is performed.

Action links

Growing community of inventors

Boulder, CO, United States of America

Thomas Archie Cook, Jr