Artificial intelligence driven personalization for content authoring applications

Patent metadata

Field	Value
Publication number	US-12050656-B2
Application number	US-202117145554-A
Country	US
Kind code	B2
Filing date	Jan 11, 2021
Priority date	Jan 11, 2021
Publication date	Jul 30, 2024
Grant date	Jul 30, 2024

Abstract

A computing system obtain a keyword and an identifier for a user of a content authoring application. Based upon the keyword and identifier for the user, the computing system walks a user graph comprising nodes connected by edges. The walk comprises identifying seed nodes in the user graph representing at least one topic that corresponds to the keyword and identifying second level nodes in the user graph that are connected to the seed nodes. The second level nodes represent first content that is associated with the user. The computing system transmits contextual data that is based upon the first content to the content authoring application. The contextual data is processed and formatted and is included in second content presentable by the content authoring application. The contextual data may be used to autogenerate the second content without user input. The second content may be modified by the user as desired.

First claim

What is claimed is:

1. A computing system, comprising:
a processor; and
memory storing instructions that, when executed by the processor, cause the processor to perform acts comprising:
obtaining a keyword and an identifier for a user of a content authoring application;
based upon the keyword and the identifier for the user, walking a computer-implemented user graph that is assigned to the user, wherein the user graph comprises nodes and edges connecting the nodes, wherein the user graph is identified from amongst several computer-implemented user graphs based upon the identifier for the user, and further wherein walking the user graph comprises:
identifying at least one seed node in the user graph, the at least one seed node representing at least one topic that corresponds to the keyword; and
identifying at least one second level node in the user graph connected to the at least one seed node via at least one edge, wherein the at least one second level node represents computer-readable first content that is associated with the user; and

transmitting contextual data to the content authoring application, wherein the contextual data is based upon the first content, and further wherein the contextual data is included in computer-readable second content that is presentable by the content authoring application.

2. The computing system of claim 1 , wherein the keyword is obtained from a user query, a topic sentence, or a title input to the content authoring application.

3. The computing system of claim 1 , the acts further comprising:
prior to obtaining the keyword and the identifier for the user, obtaining user activity data for the user from a plurality of applications, the plurality of applications including the content authoring application; and
generating the user graph based upon the user activity data.

4. The computing system of claim 1 , wherein the first content is one of:
an email;
a document;
a slideshow presentation;
a message that has been sent via a real-time messaging application; or
a spreadsheet.

5. The computing system of claim 1 , wherein the contextual data is at least a portion of the first content.

6. The computing system of claim 1 , wherein the contextual data is data that is derived from the first content.

7. The computing system of claim 6 , wherein the contextual data comprises a summary derived from the first content via application of a natural language processing (NLP) algorithm to text in the first content.

8. The computing system of claim 1 , wherein the second content presentable by the content authoring application is one of:
a slideshow presentation;
a document;
a spreadsheet;
an email; or
a message that is to be sent via a real-time messaging application.

9. The computing system of claim 1 , the acts further comprising:
based upon the keyword and the identifier for the user, identifying at least one tenancy of the user;
for each identified tenancy, walking a computer-implemented tenancy graph, wherein the tenancy graph comprises second nodes and second edges connecting the second nodes, wherein walking the tenancy graph comprises:
identifying a second at least one seed node in the tenancy graph, the second at least one seed node represents the at least one topic that corresponds to the keyword; and
identifying a second at least one second level node in the tenancy graph connected to the second at least one seed node via a second at least one edge, wherein the second at least one second level node represents computer-readable third content of the tenancy; and

transmitting second contextual data to the content authoring application, wherein the second contextual data is based upon the third content, and further wherein the second contextual data is included in the second content that is presentable by the content authoring application.

10. The computing system of claim 9 , wherein the at least one tenancy of the user is identified based upon the keyword, the identifier for the user, or access control information.

11. The computing system of claim 10 , wherein identifiers for users are selected by the user, wherein the users are to view the second content, wherein the access control information is identified based on the selected identifiers for the users, wherein walking the tenancy graph is limited based upon the access control information.

12. A method executed by a processor of a computing system, the method comprising:
obtaining a keyword and an identifier for a user of a content authoring application;
based upon the keyword and the identifier for the user, walking a computer-implemented user graph that is assigned to the user, wherein the user graph comprises nodes and edges connecting the nodes, wherein the user graph is identified from amongst several computer-implemented user graphs based upon the identifier for the user, and further wherein walking the user graph comprises:
identifying at least one seed node in the user graph, the at least one seed node representing at least one topic that corresponds to the keyword; and
identifying at least one second level node in the user graph connected to the at least one seed node via at least one edge, wherein the at least one second level node represents computer-readable first content that the user is able to access; and

transmitting contextual data to the content authoring application, wherein the contextual data is based upon the first content, and further wherein the contextual data is included in computer-readable second content that is presentable by the content authoring application.

13. The method of claim 12 , wherein walking the user graph further comprises:
identifying at least one third level node in the user graph connected to the at least one second level node via a second at least one edge, wherein the at least one third level node represents computer-readable third content that is associated with the user.

14. The method of claim 13 , further comprising:
prior to transmitting the contextual data to the content authoring application, transmitting an identifier for the first content and an identifier for the third content to the content authoring application, wherein the identifier for the first content and the identifier for the third content are presented on a display; and
receiving an indication that the identifier for the first content has been selected, wherein the contextual data includes data from the first content or data derived from the first content.

15. The method of claim 12 , wherein the at least one second level node comprises an identifier for a user data source that stores the first content and an identifier for the first content, wherein the computing system generates the contextual data by:
accessing the first content based upon the identifier for the user data source and the identifier for the first content; and
processing the first content to generate the contextual data, wherein the contextual data is stored in a contextual data store upon the content being processed.

16. The method of claim 15 , wherein processing the first content comprises executing an artificial intelligence (AI) algorithm that takes at least a portion of the first content as input, wherein the AI algorithm outputs the contextual data.

17. The method of claim 12 , wherein the at least one edge is assigned criteria that is indicative of a relationship between the at least one topic and the first content.

18. A non-transitory computer-readable storage medium comprising instructions that, when executed by a processor, cause the

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Vangala Vipindeep
• Gunda Rajesh
• Anand Rashi
• Kumar Nishchay
• Grover Sapna

Classifications

• G06F3/0481

  based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance · CPC title

• G06F40/30

  Semantic analysis · CPC title

• G06F40/279

  Recognition of textual entities · CPC title

• G06N20/00

  Machine learning · CPC title

• G06F16/9535 Primary

  Search customisation based on user profiles and personalisation · CPC title