Context driven dynamic actions embedded in messages

Patent metadata

Field	Value
Publication number	US-11082373-B1
Application number	US-202016815083-A
Country	US
Kind code	B1
Filing date	Mar 11, 2020
Priority date	Mar 11, 2020
Publication date	Aug 3, 2021
Grant date	Aug 3, 2021

Abstract

Disclosed are various approaches for dynamically creating content to present to a user based on an identified intent, or other context, associated with a message (e.g., email). A message that is received from a message server can be analyzed to identify the message content within the message prior to distributing to the recipient client device. Trained intent identification models can be applied to the identified message content to determine an intent, or other type of context, associated with the message. Upon identifying the intent, the message header can be modified to include the intent prior to forwarding the message to the recipient client device. The client device can then display a user interface including the message and a user interface element corresponding to a third-party service. The user interface element can be dynamically generated to include an action component that upon selection, triggers an action associated with the intent.

First claim

Therefore, the following is claimed:

1. A system for identifying message intent, the system comprising:
a computing device;
at least one application executable in the computing device, wherein, when executed, the at least one application causes the computing device to at least:
receive a message from a message server;
analyze the message to identify message content within the message;
identify an intent associated with the message based on one or more intent identification models and the message content;
embed the intent in a header of the message; and
transmit the message to a client device, wherein the client device renders a user interface including the message and a user interface element associated with a third-party service, the user interface element being dynamically generated to include an action component that, upon selection, triggers an action associated with the intent.

2. The system of claim 1 , wherein, when executed, the at least one application causes the computing device to at least determine an intent score based at least in part on an output of the one or more intent identification models, the intent being identified in an instance in which the intent score meets or exceeds a predefined threshold.

3. The system of claim 1 , wherein each of the one or more intent identification models are associated with a respective third-party service.

4. The system of claim 1 , wherein, when executed, the at least one application causes the computing device to parse the message content into one or more terms.

5. The system of claim 4 , wherein, when executed, the at least one application further causes the computing device to at least select the one or more intent identification models based at least in part on the one or more terms.

6. The system of claim 1 , wherein, when executed, the at least one application causes the computing device to at least upload the one or more intent identification models in response to an administrator-defined configuration.

7. The system of claim 1 , wherein, when executed, the at least one application causes the computing device to at least define a level of priority associated with the intent based at least in part on an output score of the one or more intent identification models.

8. A method for identifying message intent, the method comprising:
receiving, by a computing device, a message from a message server;
analyzing, by the computing device, the message to identify message content within the message;
identifying, by the computing device, an intent associated with the message based on one or more intent identification models and the message content;
embedding, by the computing device, the intent in a header of the message; and
transmitting, by the computing device, the message to a client device, wherein the client device renders a user interface including the message and a user interface element associated with a third-party service, the user interface element being dynamically generated to include an action component that, upon selection, triggers an action associated with the intent.

9. The method of claim 8 , further comprising determining an intent score based at least in part on an output of the one or more intent identification models, the intent being identified in an instance in which the intent score meets or exceeds a predefined threshold.

10. The method of claim 8 , wherein each of the one or more intent identification models are associated with a respective third-party service.

11. The method of claim 8 , further comprising parsing the message content into one or more terms.

12. The method of claim 11 , further comprising selecting the one or more intent identification models based at least in part on the one or more terms.

13. The method of claim 8 , further comprising uploading the one or more intent identification models in response to an administrator-defined configuration.

14. The method of claim 8 , further comprising defining a level of priority associated with the intent based at least in part on an output score of the one or more intent identification models.

15. A non-transitory computer readable medium for identifying message intent, the non-transitory, computer readable medium comprising machine-readable instructions that, when executed by a processor of a computing device, cause the computing device to at least:
receive a message from a message server;
analyze the message to identify message content within the message;
determine an intent associated with the message based on one or more intent identification models and the message content;
embed the intent in a header of the message; and
transmit the message to a client device, wherein the client device renders a user interface including the message and a user interface element associated with a third-party service, the user interface element being dynamically generated to include an action component that, upon selection, triggers an action associated with the intent.

16. The non-transitory computer readable medium of claim 15 , wherein the machine-readable instructions, when executed by the processor of the computing device, further cause the computing device to at least determine an intent score based at least in part on an output of the one or more intent identification models, the intent being identified in an instance in which the intent score meets or exceeds a predefined threshold.

17. The non-transitory computer readable medium of claim 15 , wherein each of the one or more intent identification models are associated with a respective third-party service.

18. The non-transitory computer readable medium of claim 15 , wherein the machine-readable instructions, when executed by the processor of the computing device, further cause the computing device to at least:
parse the message content into one or more terms; and
select the one or more intent identification models based at least in part on the one or more terms.

19. The non-transitory computer readable medium of claim 15 , wherein the machine-readable instructions, when executed by the processor of the computing device, further cause the computing device to at least upload the one or more intent identification models in response to an administrator-defined configuration.

20. The non-transitory computer readable medium of claim 15 , wherein the machine-readable instructions, when executed by the processor of the computing device, further cause the computing device to at least define a level of priority associated with the intent based at least in part on an output score of the one or more intent identification models.

Assignees

• Vmware Inc

Inventors

• Kochhar Arjun
• Aluvala Suman
• Maan Arvind
• Sethi Nitin
• Pilla Ramesh
• Shedigumme Shree Harsha

Classifications

• H04L51/226

  Delivery according to priorities · CPC title

• G06F40/258

  Heading extraction; Automatic titling; Numbering · CPC title

• G06F40/205

  Parsing · CPC title

• G06F40/30

  Semantic analysis · CPC title

• H04L51/18

  Commands or executable codes · CPC title