IP Library Granted Patent US 11,455,545
Granted Patent B2
US 11,455,545 · App. 15/233,881 · Granted Sep 27, 2022

Computer-implemented system and method for building context models in real time

Inventor: Simon Tucker (Oakland, CA)
Assignee: Palo Alto Research Center Incorporated
G06N5/022G06N5/025G06Q10/0639G06Q30/0201G06Q30/0202
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Quick Facts
Patent No.
US 11,455,545
App. No.
15/233,881
Granted
Sep 27, 2022
Kind
B2
Abstract

A computer-implemented system and method for building context models in real time is provided. A database of models for a user is maintained. Each model represents a contextual situation and includes one or more actions. Contextual data is collected for the user and a contextual situation is identified for that user based on the collected contextual information. Models related to the identified situation are selected and merged. One or more actions from the merged model are then selected.

Claims (56)

1. A computer-implemented system for building context models in real time, comprising:

a database of models for a user, wherein each model represents a contextual situation and comprises one or more actions of the user;

at least one mobile device comprising one of a mobile phone, smart watch, head-mounted computing device, and tablet and configured to collect contextual data of the user comprising interfacing to a global positioning system and obtaining through the global positioning system the user's location, wherein the user's location is one of a plurality of items comprised in the contextual data;

a server comprising a central processing unit, memory, an input port to receive the models from the database, and an output port, wherein the central processing unit is configured to:

identify a contextual situation for the user based on the collected contextual data from the at least one mobile device;

first, compare the contextual situation to a set of models;

determine that none of the models from the set matches the contextual situation;

identifying the contextual situation as new and not associated with the user;

second, compare at least one item of the contextual data to each of the models that does not match the contextual situation after the comparison of the contextual situation to the set of models;

select at least two models associated with contextual situations related to the identified contextual situation determined from the user's contextual data, wherein the contextual situations of the at least two models are related to the contextual situation of the user and the selected models each comprise significance values of the actions associated with the contextual situation of that model;

merging the selected models for the identified contextual situation of the user as a merged model, wherein merging the selected models comprises adding, averaging, or determining a median of the significance values of common actions of the selected models to generate new significance values for the common actions;

designate the merged model as a new model for the identified contextual situation of the user;

identifying actions from the merged model that are most performed by the user for one or more of the contextual situations associated with the selected models of the merged model, wherein the most performed actions are determined based on the significance values of the actions for the merged model;

automatically select one or more of the most performed actions from the merged model for the contextual situation; and

provide the one or more selected actions to the user, wherein the user performs one of the selected actions during the contextual situation; and

the at least one mobile device configured to display the one or more selected actions.

2. The system according to claim 1 , wherein the central processing unit assigns the merged model to the identified contextual situation.

3. The system according to claim 1 , wherein the models are selected based on a similarity to the identified contextual situation.

4. The system according to claim 3 , wherein the central processing unit determines the similarity between each model and the identified contextual situation based on one or more of location, time, goal, action, and recommendation.

5. The system according to claim 1 , wherein the contextual data comprises one or more of time, location, date, day, temperature, vital sign, and acceleration.

6. The system according to claim 1 , wherein the central processing unit delivers one or more of the selected actions from the merged model to the user as a recommendation.

7. The system according to claim 6 , wherein each recommendation comprises one or more of a link, directions, location, and instructions.

8. The system according to claim 1 , wherein the central processing unit identifies as the most performed actions those actions with higher significance values.

9. The system according to claim 1 , wherein the central processing unit identifies the selected actions by counting an occurrence of each action and choosing as the selected actions those actions with higher occurrences.

10. The system according to claim 1 , wherein the merged model covers the contextual situations associated with the selected models of the merged model across different times and locations.

11. A computer-implemented method for building context models in real time, comprising:

maintaining a database of models for a user, wherein each model represents a contextual situation and comprises one or more actions;

collecting contextual data for the user via a mobile device comprising one or more of a mobile phone, smart watch, head-mounted computing device, and tablet, the mobile device configured to collect contextual data of the user comprising interfacing to a global positioning system and obtaining through the global positioning system the user's location, wherein the user's location is one of many items comprised in the contextual data;

identifying a contextual situation for the user based on the collected contextual data;

first, comparing the contextual situation to a set of models;

determining none of the models from the set matches the contextual situation;

identifying the contextual situation as new and not associated with the user;

second, comparing at least one item of the contextual data to each of the models that does not match the contextual situation after the comparison of the contextual situation to the set of models;

selecting two or more models associated with contextual situations related to the identified contextual situation determined from the user's contextual data, wherein the contextual situations of the at least two models are related to the contextual situation of the user and the selected models each comprise significance values of the actions associated with the contextual situation of that model;

merging the selected models for the identified contextual situation of the user, wherein merging the selected models comprises adding, averaging, or determining a median of the significance values of common actions of the selected models to generate new significance values for the common actions;

designating the merged model as a new model for the identified contextual situation of the user;

identifying actions from the merged model that are most performed by the user for one or more of the contextual situations associated with the selected models of the merged model, wherein the most performed actions are determined based on the significance values of the actions for the merged model;

selecting one or more actions of the most performed from the merged model for the contextual situation;

providing the one or more selected actions to the user, wherein the user performs one of the selected actions during the contextual situation; and

displaying on the at least one mobile device the one or more selected actions.

12. The method according to claim 11 , further comprising:

assigning the merged model to the identified contextual situation.

13. The method according to claim 11 , wherein the models are selected based on a similarity to the identified contextual situation.

14. The method according to claim 13 , further comprising:

determining the similarity between each model and the identified contextual situation based on one or more of location, time, goal, action, and recommendation.

15. The method according to claim 11 , wherein the contextual data comprises one or more of time, location, date, day, temperature, vital sign, and acceleration.

16. The method according to claim 11 , further comprising:

delivering one or more of the selected actions from the merged model to the user as a recommendation.

17. The method according to claim 16 , wherein each recommendation comprises one or more of a link, directions, location, and instructions.

18. The method according to claim 11 , further comprising:

identifying as the most performed actions those actions with higher significance values.

19. The method according to claim 11 , further comprising:

identifying the selected actions, comprising:

counting an occurrence of each action; and

choosing as the selected actions those actions with higher occurrences.

20. The method according to claim 11 , wherein the merged model covers the contextual situations associated with the selected models of the merged model across different times and locations.

Assignments (10)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 14, 2025
From: XEROX CORPORATION
To: GENESEE VALLEY INNOVATIONS, LLC
Reel/Frame 073562/0677 →
SECOND LIEN NOTES PATENT SECURITY AGREEMENT Recorded Jul 2, 2025
From: XEROX CORPORATION
To: U.S. BANK TRUST COMPANY, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
Reel/Frame 071785/0550 →
FIRST LIEN NOTES PATENT SECURITY AGREEMENT Recorded Apr 11, 2025
From: XEROX CORPORATION
To: U.S. BANK TRUST COMPANY, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
Reel/Frame 070824/0001 →
TERMINATION AND RELEASE OF SECURITY INTEREST IN PATENTS RECORDED AT RF 064760/0389 Recorded Feb 13, 2024
From: CITIBANK, N.A., AS COLLATERAL AGENT
To: XEROX CORPORATION
Reel/Frame 068261/0001 →
SECURITY INTEREST Recorded Feb 13, 2024
From: XEROX CORPORATION
To: CITIBANK, N.A., AS COLLATERAL AGENT
Reel/Frame 066741/0001 →
SECURITY INTEREST Recorded Nov 20, 2023
From: XEROX CORPORATION
To: JEFFERIES FINANCE LLC, AS COLLATERAL AGENT
Reel/Frame 065628/0019 →
CORRECTIVE ASSIGNMENT TO CORRECT THE REMOVAL OF US PATENTS 9356603, 10026651, 10626048 AND INCLUSION OF US PATENT 7167871 PREVIOUSLY RECORDED ON REEL 064038 FRAME 0001. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Jun 28, 2023
From: PALO ALTO RESEARCH CENTER INCORPORATED
To: XEROX CORPORATION
Reel/Frame 064161/0001 →
SECURITY INTEREST Recorded Jun 22, 2023
From: XEROX CORPORATION
To: CITIBANK, N.A., AS COLLATERAL AGENT
Reel/Frame 064760/0389 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 20, 2023
From: PALO ALTO RESEARCH CENTER INCORPORATED
To: XEROX CORPORATION
Reel/Frame 064038/0001 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 11, 2016
From: TUCKER, SIMON
To: PALO ALTO RESEARCH CENTER INCORPORATED
Reel/Frame 039406/0479 →
Continuity (1)
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