IP Library Granted Patent US 11,429,262
Granted Patent B2
US 11,429,262 · App. 17/304,362 · Granted Aug 30, 2022

Systems and methods for determining and displaying optimal associations of data items

Inventors: Lucas Lemanowicz (New York, NY); Yehonatan Steinmetz (Brooklyn, NY); Ashwin Sreenivas (New York, NY); Daniel Spangenberger (New York, NY); Tinlok Pang (New York, NY)
Assignee: Palantir Technologies Inc.
G06F3/04842G06F9/451G06F16/435
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Quick Facts
Patent No.
US 11,429,262
App. No.
17/304,362
Granted
Aug 30, 2022
Kind
B2
Abstract

Systems and methods are described for determining and displaying optimal associations of data items. Data items may include media content such as television programs, and may be associated with advertisements to be displayed during content consumption. A tool may process data regarding segments of viewers that have common characteristics, and further process data regarding viewers of particular data items, to identify degrees of association between individual segments of viewers and particular data items. The degrees of association between a particular data item and multiple segments of viewers, or between multiple data items and a particular segment of viewers, may be displayed in a user interface that identifies optimal associations between data items and advertisements based on the viewer segments having high degrees of association with the data item.

Claims (40)

1. A system comprising:

a data store configured to store computer-executable instructions; and

a processor in communication with the data store, wherein the computer-executable instructions, when executed by the processor, configure the processor to perform operations including:

accessing first data identifying a plurality of segments of consumers of media content, wherein each segment in the plurality of segments corresponds to a characteristic associated with each consumer in the segment;

accessing second data identifying a plurality of consumers of media content, wherein individual consumers in the plurality of consumers of media content consumed a content item from a specified source at a specified date and time;

determining, based at least in part on the plurality of segments of consumers and the plurality of consumers, a degree of association between the characteristic associated with a first segment of consumers and individual content items;

generating a user interface for display, wherein the user interface enables selection of one or more characteristics associated with consumers, and wherein the user interface includes the degree of association between the selected one or more characteristics and one or more content items; and

causing display of the user interface.

2. The system of claim 1 , wherein the media content comprises one of more of television programs, radio broadcasts, movies, webcasts, podcasts, streaming media content, social media content, or online content.

3. The system of claim 1 , wherein the specified source comprises one or more of a television network, radio station, movie studio, webcast, podcast, online content provider, social media platform, mobile application, or video game.

4. The system of claim 1 , wherein the data store is configured to store further computer-executable instructions that, when executed by the processor, configure the processor to perform further operations including:

generating a second user interface for display, wherein the second user interface enables selection of one or more content items, and wherein the second user interface includes the degree of association the selected one or more content items and one or more characteristics associated with consumers.

5. The system of claim 1 , wherein the user interface enables selection of a first characteristic and a second characteristic.

6. The system of claim 5 , wherein the data store is configured to store further computer-executable instructions that, when executed by the processor, configure the processor to perform further operations including:

identifying, as a new segment of consumers of media content, a union or intersection of a first segment of consumers corresponding to the first characteristic and a second segment of consumers corresponding to the second characteristic;

determining, based at least in part on degrees of association between individual content items and the first and second segments, degrees of association between individual content items and the new segment; and

causing display, in the user interface, of one or more degrees of association between individual content items and the new segment.

7. A computer-implemented method comprising:

obtaining first data identifying a plurality of segments of consumers of media content, wherein each segment in the plurality of segments corresponds to a characteristic associated with each consumer in the segment;

obtaining second data identifying a plurality of consumers of content items, wherein individual consumers in the plurality of consumers consumed at least a portion of a content item;

determining, based at least in part on the plurality of segments of consumers and the plurality of consumers of content items, a degree of association between the characteristic associated with a first segment of consumers and the content item;

generating a user interface for display, wherein the user interface enables selection of one or more characteristics associated with consumers, and wherein the user interface includes the degree of association between the selected one or more characteristics associated with the first segment of consumers and the content item; and

causing display of the user interface.

8. The computer-implemented method of claim 7 further comprising identifying the content item based at least in part on a specified source, date, and time.

9. The computer-implemented method of claim 7 further comprising determining a degree of association between the characteristic associated with the first segment of consumers and a first portion of the content item.

10. The computer-implemented method of claim 7 , wherein the content item is associated with a day and time.

11. The computer-implemented method of claim 10 , wherein the day and time correspond to when the content item is first made available, and wherein at least a portion of the plurality of consumers consume the content item at other days and times.

12. The computer-implemented method of claim 11 , wherein the user interface enables selection from a plurality of day and time ranges, and wherein each of the plurality of day and time ranges is associated with a different subset of the plurality of consumers of the content item.

13. The computer-implemented method of claim 7 , wherein the user interface enables selection of a time period.

14. The computer-implemented method of claim 13 , wherein the time period comprises one or more of a year, quarter, month, week, day, day of the week, sports season, or irregular time period.

15. The computer-implemented method of claim 7 , wherein the degree of association between the characteristic associated with the first segment of consumers and the content item is determined using a term frequency-inverse document frequency function.

16. A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a processor, configure the processor to perform operations including:

determining, based at least in part on first data identifying a plurality of segments of consumers of content items and second data identifying a plurality of consumers of content items, a degree of association between characteristics associated with each consumer in individual segments of the plurality of segments and a first content item of a plurality of content items;

generating a user interface for display, wherein the user interface enables selection of one or more characteristics associated with consumers of content items, and wherein the user interface includes a degree of association between the selected one or more characteristics associated with each consumer in the individual segments of the plurality of segments and the first content item of the plurality of content items; and

causing display of the user interface.

17. The non-transitory computer-readable medium of claim 16 , wherein the user interface enables selection from a plurality of data sources.

18. The non-transitory computer-readable medium of claim 17 , wherein each of the plurality of data sources is associated with a respective time period.

19. The non-transitory computer-readable medium of claim 16 , wherein the second data includes characteristics associated with individual consumers of content items.

20. The non-transitory computer-readable medium of claim 19 storing further computer-executable instructions that, when executed by the processor, configure the processor to perform further operations including:

generating the first data based at least in part on the second data.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 27, 2023
From: LEMANOWICZ, LUCAS; STEINMETZ, YEHONATAN; SREENIVAS, ASHWIN; SPANGENBERGER, DANIEL; PANG, TINLOK
To: PALANTIR TECHNOLOGIES INC.
Reel/Frame 064404/0833 →
SECURITY INTEREST Recorded Jul 3, 2022
From: PALANTIR TECHNOLOGIES INC.
To: WELLS FARGO BANK, N.A.
Reel/Frame 060572/0506 →
Continuity (3)
Continuation 16428461 · May 31, 2019
Provisional Application 62679614 · Jun 1, 2018
Related Publication 20210311612A1 · Oct 7, 2021