IP Library Granted Patent US 11,989,175
Granted Patent B2
US 11,989,175 · App. 17/935,201 · Granted May 21, 2024

Systems and methods for customizing electronic information cards with context data

Inventors: Scott Rigney (Bristow, VA); Michael-Andrew Keays (Annandale, VA); Malik Abu-Kalokoh (Fort Washington, MD); Utkarsha Bhave (Tysons Corner, VA)
Assignee: MICROSTRATEGY INCORPORATED
G06F16/2423G06N20/00
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Quick Facts
Patent No.
US 11,989,175
App. No.
17/935,201
Granted
May 21, 2024
Kind
B2
Abstract

Methods, systems, and apparatus, including computer programs stored on computer-readable media, for generating context data for an information card are disclosed. Upon receiving a selection of a data element to include in an information card, a plurality of dimensional view types available for the data element are determined and provided to a user. Upon receiving a selection of a dimensional view type from the plurality of dimensional view types, a set of attributes associated with the dimensional view type are determined and provided to the user. A selection of an attribute from the set of attributes is received, and a dimensional view is generated based on the selection of the dimensional view type and attribute.

Claims (66)

1. A computer-implemented method of generating context data for an information card, the method comprising:

receiving a selection of a data element to include in an information card relating to a particular entity, wherein the information card is configured for display based on a detection of a keyword associated with the particular entity;

determining a plurality of data analysis types available for the data element;

providing the plurality of data analysis types to an artificial intelligence machine learning model, wherein the artificial intelligence machine learning model is trained using previous data analysis type selections;

receiving, from the artificial intelligence machine learning model, a machine learning output comprising a first data analysis type, from the plurality of data analysis types;

determining a first set of attributes associated with the first data analysis type;

providing the first set of attributes;

receiving a selection of a first attribute from the first set of attributes; and

generating a first data analysis based on the selection of the first data analysis type and first attribute.

2. The computer-implemented method of claim 1 , wherein the machine learning output comprises a second data analysis type and further comprising:

determining a second set of attributes associated with the second data analysis type;

providing the second set of attributes;

receiving a selection of a second attribute from the second set of attributes; and

generating a second data analysis based on the selection of the second data analysis type and second attribute.

3. The computer-implemented method of claim 2 , wherein the first data analysis and the second data analysis is configured for display using a time-automated scrolling dock.

4. The computer-implemented method of claim 1 , further comprising causing for display the first data analysis, within the information card.

5. The computer-implemented method of claim 1 , further comprising detecting user interaction with the data element, wherein the plurality of data analysis types available for the data element are determined upon detecting the user interaction with the data element.

6. The computer-implemented method of claim 1 , wherein the first set of attributes are provided in a card creation user interface.

7. The computer-implemented method of claim 6 , wherein the first set of attributes are provided in a card presentation user interface, the card presentation user interface being generated based on the card creation user interface.

8. The computer-implemented method of claim 1 , wherein the plurality of data analysis types comprise more than one of a percent change, a rank, a trend line, or a breakdown.

9. The computer-implemented method of claim 1 , wherein the first set of attributes comprise one of: time attributes or non-time attributes.

10. The computer-implemented method of claim 1 , wherein the first data analysis type and first attribute are stored as part of card data defining the information card, and the first data analysis is generated based on the card data.

11. The computer-implemented method of claim 1 , further comprising:

providing a plurality of time intervals;

receiving a selection of a time interval from the plurality of time intervals; and

sequentially displaying the first data analysis based on the time interval.

12. A computer-implemented method of generating context data for an information card, the method comprising:

receiving a selection of a data element to include in an information card relating to a particular entity, wherein the information card is configured for display based on a detection of a keyword associated with the particular entity;

determining a plurality of data analysis types available for the data element;

providing the plurality of data analysis types;

receiving a selection of a first data analysis type, from the plurality of data analysis types;

determining a first set of attributes associated with the first data analysis type;

providing the first set of attributes;

receiving a selection of a first attribute from the first set of attributes; and

generating a first data analysis based on the selection of the first data analysis type and first attribute.

13. The computer-implemented method of claim 12 , further comprising:

receiving a selection of a second data analysis type, from the plurality of data analysis types;

determining a second set of attributes associated with the second data analysis type;

providing the second set of attributes;

receiving a selection of a second attribute from the second set of attributes; and

generating a second data analysis based on the selection of the second data analysis type and second attribute.

14. The computer-implemented method of claim 13 , further comprising:

providing a plurality of time intervals;

receiving a selection of a time interval from the plurality of time intervals; and

sequentially displaying the first data analysis and the second data analysis based on the time interval.

15. The computer-implemented method of claim 12 , wherein the first data analysis type and first attribute are stored as part of card data defining the information card, and the first data analysis is generated based on the card data.

16. The computer-implemented method of claim 12 , wherein the first set of attributes associated with the first data analysis type are determined using a machine learning model.

17. The computer-implemented method of claim 12 , wherein the plurality of data analysis types and the first set of attributes are provided in one of: a card creation user interface or a card presentation user interface.

18. The computer-implemented method of claim 12 , wherein the plurality of data analysis types comprise more than one of: a percent change, a rank, a trend line, and a breakdown.

19. A system comprising:

one or more processors; and

one or more computer-readable media comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform operations for generating context data for an information card, the operations comprising:

receiving a selection of a data element to include in an information card relating to a particular entity, wherein the information card is configured for display based on detection of a keyword associated with the particular entity;

determining a plurality of data analysis types available for the data element;

providing the plurality of data analysis types;

receiving a selection of a first data analysis type, from the plurality of data analysis types;

determining a first set of attributes associated with the first data analysis type;

providing the first set of attributes;

receiving a selection of a first attribute from the first set of attributes; and

generating a first data analysis based on the selection of the first data analysis type and first attribute.

20. The system of claim 19 , wherein the operations further comprise:

receiving a selection of a second data analysis type, from the plurality of data analysis types;

determining a second set of attributes associated with the second data analysis type;

providing the second set of attributes;

receiving a selection of a second attribute from the second set of attributes; and

generating a second data analysis based on the selection of the second data analysis type and second attribute, wherein the first data analysis and the second data analysis is configured for display within the information card.

Assignments (4)
CHANGE OF NAME Recorded Aug 19, 2025
From: MICROSTRATEGY INCOPORATED
To: STRATEGY INC
Reel/Frame 072513/0437 →
TERMINATION AND RELEASE OF PATENT SECURITY AGREEMENT AT REEL/FRAME: 056647/0687, REEL/FRAME: 057435/0023, REEL/FRAME: 059256/0247, REEL/FRAME: 062794/0255 AND REEL/FRAME: 066663/0713 Recorded Sep 26, 2024
From: U.S. BANK TRUST COMPANY, NATIONAL ASSOCIATION, AS SUCCESSOR IN INTEREST TO U.S. BANK NATIONAL ASSOCIATION, IN ITS CAPACITY AS COLLATERAL AGENT FOR THE SECURED PARTIES
To: MICROSTRATEGY INCORPORATED; MICROSTRATEGY SERVICES CORPORATION
Reel/Frame 069065/0539 →
SUPPLEMENTARY PATENT SECURITY AGREEMENT Recorded Feb 17, 2023
From: MICROSTRATEGY INCORPORATED; MICROSTRATEGY SERVICES CORPORATION
To: U.S. BANK TRUST COMPANY, NATIONAL ASSOCIATION, AS SUCCESSOR IN INTEREST TO U.S. BANK NATIONAL ASSOCIATION, IN ITS CAPACITY AS COLLATERAL AGENT FOR THE SECURED PARTIES
Reel/Frame 062794/0255 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 28, 2022
From: RIGNEY, SCOTT; KEAYS, MICHAEL-ANDREW; ABU-KALOKOH, MALIK; BHAVE, UTKARSHA
To: MICROSTRATEGY INCORPORATED
Reel/Frame 061585/0573 →