Semantic navigation of content documents

Patent metadata

Field	Value
Publication number	US-11630939-B2
Application number	US-202117450356-A
Country	US
Kind code	B2
Filing date	Oct 8, 2021
Priority date	Jan 27, 2020
Publication date	Apr 18, 2023
Grant date	Apr 18, 2023

Abstract

A computer-implemented method may be used for semantic navigation of content. The method may include determining a first content complexity level for a user, and presenting a first content to a user device operated by the user. The first content may be presented at the first content complexity level of the user. Additionally, the method may include receiving a navigation command from the user on a portion of the first content via the user device; and determining a second content at a second content complexity level based on the navigation command. The second content may convey the same information as the first content. Additionally, the method may include replacing the first content with the second content on the user device. The second content may be presented at the second content complexity level, and the second content complexity level may be different than the first content complexity level.

First claim

What is claimed is:

1. A computer-implemented method of semantic navigation of content utilizing machine learning, the method comprising:
receiving, by a processor, first data that includes first information associated with previous interactions between a user and at least one content item, the first information including at least one of a position of the user or one or more contents created by the user;
predicting, via a trained machine learning model executed by the processor and based on the first data, a first content complexity level for the user, wherein:
the trained machine learning model is trained, based on (i) second data that includes second information associated with previous interactions between one or more persons and one or more content items as test data, and (ii) third data that includes complexity levels for the one or more persons, and
the second information includes at least one of job titles of the one or more persons or one or more contents created by the one or more persons; and

generating, by the processor, a first content for presentation via a user device, wherein the first content is at the first content complexity level of the user.

2. The computer-implemented method of claim 1 , wherein the first information further includes one or more previous user navigation commands or one or more user preferences.

3. The computer-implemented method of claim 2 , further comprising:
adjusting, by the processor, the first content complexity level of the user upon a detected change in at least one of the position of the user, the one or more contents created by the user, the one or more previous user navigation commands, or the one or more user preferences.

4. The computer-implemented method of claim 1 , wherein the first content includes at least one of an Uniform Resource Locator (URL), a text document, or an image.

5. The computer-implemented method of claim 1 , further including:
receiving a navigation command from the user via the user device on a portion of the first content; and
tagging the portion of the first content, wherein a second content is related to the portion of the first content via the tagging.

6. The computer-implemented method of claim 5 , wherein the first content is disparate from the second content such that the second content includes at least one of an Uniform Resource Locator (URL), a text document, or an image disparate from the first content.

7. The computer-implemented method of claim 5 , wherein the navigation command is at least one of a zoom-in, a zoom-out, or a pinch gesture.

8. The computer-implemented method of claim 1 , further comprising:
determining, by the processor, a second content at a second content complexity level, wherein the second content conveys a same information as the first content; and
causing replacing, by the processor, of the first content with the second content at the user device, wherein:
the second content is at the second content complexity level, wherein the second content complexity level is different than the first content complexity level; and
the causing the replacing of the first content with the second content at the user device further includes causing presentation of the second content as a pop-up on top of the first content.

9. The computer-implemented method of claim 1 , wherein the user device is a type of user device selected from at least one of a laptop, a desktop, a mobile phone, a tablet, an e-reader, or a wearable.

10. The computer-implemented method of claim 9 further including:
causing display, by the one or more processors, of instructions pertaining to a navigation command based on the type of the user device.

11. A computer system for semantic navigation of content, the computer system comprising:
a memory having processor-readable instructions stored therein; and
at least one processor configured to access the memory and execute the processor-readable instructions, which when executed by the processor configures the processor to perform a plurality of functions, including functions for:
receiving, by a processor, first data that includes first information associated with previous interactions between a user and at least one content item, the first information including at least one of a position of the user or one or more contents created by the user;
predicting, via a trained machine learning model executed by the processor and based on the first data, a first content complexity level for the user, wherein:
the trained machine learning model is trained, based on (i) second data that includes second information associated with previous interactions between one or more persons and one or more content items as test data, and (ii) third data that includes complexity levels for the one or more persons, and
the second information includes at least one of job titles of the one or more persons or one or more contents created by the one or more persons; and

generating, by the processor, a first content for presentation via a user device, wherein the first content is at the first content complexity level of the user.

12. The computer system of claim 11 , wherein the first information further includes one or more previous user navigation commands or one or more user preferences.

13. The computer system of claim 12 , wherein the plurality of functions further includes:
adjusting the first content complexity level of the user upon a detected change in at least one of the position of the user, the one or more contents created by the user, the one or more previous user navigation commands, or the one or more user preferences.

14. The computer system of claim 12 , wherein the one or more previous user navigation commands is at least one of a zoom-in, a zoom-out, or a pinch gesture.

15. The computer system of claim 11 , wherein the first content includes at least one of an Uniform Resource Locator (URL), a text document, or an image.

16. The computer system of claim 11 , wherein the first content is disparate from a second content such that the second content includes at least one of an Uniform Resource Locator (URL), a text document, or an image disparate from the first content.

17. The computer system of claim 11 , wherein the plurality of functions further include:
determining a second content at a second content complexity level, wherein the second content conveys the same information as the first content; and
causing replacing of the first content with the second content on the user device, wherein:
the second content is at the second content complexity level, wherein the second content complexity level is different than the first content complexity level; and
the causing replacing of the first content with the second content on the user device further includes causing presentation of the second content as a pop-up on top of the first content.

18. The computer system of claim 11 , wherein the user device is a type of user device selected from at least one of a laptop, a desktop, a mobile phone, a tablet, an e-reader, or a wearable.

19. The computer system of claim 18 , further including, displaying instructions pertaining to a navigation command based on the type of the user device.

20. A computer-implemented method of semantic navigation of content, the method comprising:
receiving, by a processor, first data that includes first information associated with previous interactions between a user and at least one content item, the first information including at least one of a position of the user

Assignees

• Capital One Services Llc

Inventors

• Gray Brian

Classifications

• G06F40/106 Primary

  Display of layout of documents; Previewing · CPC title

• G06F3/04845

  for image manipulation, e.g. dragging, rotation, expansion or change of colour · CPC title

• G06F40/30 Primary

  Semantic analysis · CPC title