Integration of personalized dynamic web feed experiences into operating system shell surfaces

Patent metadata

Field	Value
Publication number	US-11392279-B2
Application number	US-202117148912-A
Country	US
Kind code	B2
Filing date	Jan 14, 2021
Priority date	Nov 16, 2020
Publication date	Jul 19, 2022
Grant date	Jul 19, 2022

Abstract

Systems, methods and devices for surfacing web content in an operating system shell construct are provided. A taskbar web content element size may be selected based on an amount of free space in a taskbar. First and second scored web content may be received, wherein the web content is scored based at least on the web content's relevance score to a first user account. A taskbar web content topical display category corresponding to the first web content may be selected based on the first web content having a higher score than the second web content. A web content element of the selected size and topical display category may be caused to be surfaced in the taskbar. A selection of the surfaced web content element may be received and a subset of the first web content form the first source may be caused to be surfaced in a web content pane.

First claim

What is claimed is:

1. A computer-implemented method for surfacing web content in an operating system shell construct, the computer-implemented method comprising:
determining an amount of free space in a taskbar on a user interface;
selecting a taskbar web content element size based on the determined amount of free space in the taskbar, wherein the web content element size is selected from a first size having a first amount of information, and a second size having a second amount of information;
receiving scored first web content from a first source and scored second web content from a second source, wherein the web content is scored based at least on the web content's relevance score to a first user account;
selecting a taskbar web content topical display category corresponding to the first web content based on the first web content having a higher score than the second web content; and
causing a first web content element of the selected size and the topical display category to be surfaced in the taskbar on the user interface.

2. The computer-implemented method of claim 1 , further comprising:
receiving a selection of the surfaced first web content element; and
causing, based on receiving the selection, a subset of the first web content from the first source to be surfaced in a web content pane.

3. The computer-implemented method of claim 2 , further comprising:
receiving a selection of the subset of the first web content in the web content pane; and
automatically causing a webpage corresponding to the first source to be opened and displayed in a web browser application.

4. The computer-implemented method of claim 1 , further comprising:
periodically receiving web content from a web content feeds service;
caching the web content on a computing device on which the taskbar resides;
determining that an internet connection is currently unavailable;
determining that a content rotation temporal threshold has elapsed; and
causing a new web content element corresponding to web content cached on the computing device to be displayed in the taskbar on the user interface.

5. The computer-implemented method of claim 1 , further comprising:
receiving scored third web content;
determining that the score for the third web content is above a threshold value; and
causing, based on the score for the third web content being above the threshold value, the first web content element to be replaced in the taskbar by a second web content element corresponding to the third web content.

6. The computer-implemented method of claim 5 , further comprising:
selecting, based on the score for the third web content being above the threshold value, a different taskbar web content topical display category corresponding to the third web content.

7. The computer-implemented method of claim 6 , wherein the second web content element has the selected size and the different topical taskbar web content topical display category.

8. The computer-implemented method of claim 1 , further comprising:
calculating a score for the first web content, the calculating comprising:
determining a geographic relevance of the first web content to the first user account;
determining a demographic relevance of the first web content to the first user account;
determining a trending value of the first web content;
determining a temporal freshness value of the first web content;
determining a social graph value of the first web content in relation to the first user account; and
determining a topical match value of the first web content in relation to topical categories of interest for the first user account.

9. The computer-implemented method of claim 1 , further comprising:
categorizing the first web content, the categorizing comprising applying an image neural network to a webpage corresponding to the first source, wherein the image neural network has been trained to classify web content into topical categories.

10. The computer-implemented method of claim 1 , further comprising:
categorizing the first web content, the categorizing comprising applying a natural language processing model to text of a webpage corresponding to the first source, wherein the natural language processing model is an embedding model that has been trained to classify text into topical categories.

11. The computer-implemented method of claim 1 , further comprising:
categorizing the first web content, the categorizing comprising analyzing a header of a webpage corresponding to the first source.

12. A system for surfacing web content in an operating system shell construct, comprising:
a memory for storing executable program code; and
a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative to:
determine an amount of free space in a taskbar on a user interface;
select a taskbar web content element size based on the determined amount of free space in the taskbar, wherein the web content element size is selected from a first size having a first amount of information, and a second size having a second amount of information;
receive scored first web content from a first source and scored second web content from a second source, wherein the web content is scored based at least on the web content's relevance score to a first user account;
select a taskbar web content topical display category corresponding to the first web content based on the first web content having a higher score than the second web content; and
cause a first web content element of the selected size and the topical display category to be surfaced in the taskbar on the user interface.

13. The system of claim 12 , wherein the processor is further responsive to the computer-executable instructions contained in the program code and operative to:
receive a selection of the surfaced first web content element; and
cause, based on receiving the selection, a subset of the first web content from the first source to be surfaced in a web content pane.

14. The system of claim 13 , wherein the processor is further responsive to the computer-executable instructions contained in the program code and operative to:
receive a selection of the subset of the first web content in the web content pane; and
automatically cause a webpage corresponding to the first source to be opened and displayed in a web browser application.

15. The system of claim 12 , wherein the processor is further responsive to the computer-executable instructions contained in the program code and operative to:
periodically receive web content from a web content feeds service;
cache the web content on a computing device on which the taskbar resides;
determine that an internet connection is currently unavailable;
determine that a content rotation temporal threshold has elapsed; and
cause a new web content element corresponding to web content cached on the computing device to be displayed in the taskbar on the user interface.

16. The system of claim 12 , wherein the processor is further responsive to the computer-executable instructions contained in the program code and operative to:
categorize the first web content, the categorizing comprising applying an image neural network to a webpage corresponding to the first source, wherein the image neural network has been trained to classify web content into topical categories.

17. The system of claim 12 , wherein the processor is further responsive to the computer-executable instructions contained in the program code and operative to:

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Campbell Alexander Leo
• Xue Shengbo
• Saunders Dena Natalie
• Frye Robert David
• Varanda Julian Manuel
• Singley Bradford Glenn
• Basilio Camille Dominique
• Mclaughlin Hanna
• Feng Dorothy
• Chen Arthur
• Rueda Guillermo Enrique
• Doggett Chani Ayn
• Amar Nassim
• Ma Bojun
• Motevaselolhagh Houman

Classifications

• G06N3/044

  Recurrent networks, e.g. Hopfield networks · CPC title

• G06N3/045

  Combinations of networks · CPC title

• G06N3/0464

  Convolutional networks [CNN, ConvNet] · CPC title

• 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

• G06F9/451

  Execution arrangements for user interfaces · CPC title