IP Library Granted Patent US 11,601,694
Granted Patent B1
US 11,601,694 · App. 17/544,644 · Granted Mar 7, 2023

Real-time content data processing using robust data models

Inventors: Dmitriy Karpman (San Francisco, CA); Kevin Guo (San Francisco, CA); Ryan Weber (San Francisco, CA)
Assignee: CASTLE GLOBAL, INC.
H04N21/23418H04N21/2353G06V20/41G06V20/70G10L15/08
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Quick Facts
Patent No.
US 11,601,694
App. No.
17/544,644
Granted
Mar 7, 2023
Kind
B1
Abstract

A system stores a plurality of data models, each data model being configured to sort datasets based on a set of criteria unique to the data model. The system further identifies a plurality of content streams on a plurality of content streaming platforms. The system then executes each data model of the plurality of data models on each content stream of the plurality of content streams to generate a labeled content file of each content stream of the plurality of content streams.

Claims (52)

1. A computing system comprising:

a database storing a plurality of data models, each data model being configured to sort datasets based on a set of criteria unique to the data model;

one or more processors; and

a memory resource storing instructions that, when executed by the one or more processors, cause the computing system to:

receive a content policy from a content streaming platform on which a plurality of live content streams are provided simultaneously to a plurality of users, the content policy identifying a plurality of moderated content characteristics;

implement, in real-time, a content moderation service for the content streaming platform that is based on the content policy, by:

processing the plurality of live content streams of the content streaming platform;

for each live content stream of the plurality of live content streams, (i) executing a multi-headed model that utilizes the plurality of data models to identify each content characteristic of the plurality of moderated content characteristics that is present in the live content stream; and (ii) generating a labeled content file that indicates each identified content characteristic of the plurality of moderated content characteristics; and

for at least a first live content stream of the plurality of live content streams, automatically performing an action, without user input, in response to detecting that the first live content stream of the plurality of live content streams includes one or more of the plurality of moderated content characteristics;

wherein the automatically performed action comprises transmitting the labeled content file to a computing device of the content streaming platform.

2. The computing system of claim 1 , wherein the set of criteria unique to each data model corresponds to at least one of classifying or labeling elements in content data of each of the plurality of live content streams.

3. The computing system of claim 1 , wherein the automatically performed action further comprises at least one of transmitting a notification to a computing device of the content streaming platform or transmitting a command to shut down the first live content stream.

4. The computing system of claim 1 , wherein the first live content stream of the plurality of live content streams includes advertisements, and wherein the executed instructions further cause the computing system to:

determine, based on executing each data model of the plurality of data models on the first live content stream, a current advertising category for the first live content stream; and

select, for presentation on the first live content stream, one or more advertisements from a plurality of labeled advertisements in a database that match the current advertising category of the first live content stream.

5. The computing system of claim 4 , wherein the first live content stream includes one or more advertising breaks in the first live content stream, and wherein the executed instructions cause the computing system to select the one or more advertisements in real-time for an upcoming advertisement break in the first live content stream.

6. A non-transitory computer readable medium storing instructions that, when executed by one or more processors of a computing system, cause the computing system to:

store, in a database, a plurality of data models, each data model being configured to sort datasets based on a set of criteria unique to the data model;

receive a content policy from a content streaming platform on which a plurality of live content streams are provided simultaneously to a plurality of users, the content policy identifying a plurality of moderated content characteristics;

implement, in real-time, a content moderation service for the content streaming platform that is based on the content policy, by:

processing the plurality of live content streams of the content streaming platform;

for each live content stream of the plurality of live content streams, (i) executing a multi-headed model that utilizes the plurality of data models to identify each content characteristic of the plurality of moderated content characteristics that is present in the live content stream; and (ii) generating a labeled content file that indicates each identified content characteristic of the plurality of moderated content characteristics; and

for at least a first live content stream of the plurality of live content streams, automatically performing an action, without user input, in response to detecting that the first live content stream of the plurality of live content streams includes one or more of the plurality of moderated content characteristics;

wherein the automatically performed action comprises transmitting the labeled content file to a computing device of the content streaming platform.

7. The non-transitory computer readable medium of claim 6 , wherein the set of criteria unique to each data model corresponds to at least one of classifying or labeling elements in content data of each of the plurality of live content streams.

8. The non-transitory computer readable medium of claim 6 , wherein the automatically performed action comprises at least one of transmitting a notification to a computing device of the content streaming platform or transmitting a command to shut down the first live content stream.

9. The non-transitory computer readable medium of claim 6 , wherein the first live content stream of the plurality of live content streams includes advertisements, and wherein the executed instructions further cause the computing system to:

determine, based on executing each data model of the plurality of data models on the first live content stream, a current advertising category for the first live content stream; and

select, for presentation on the first live content stream, one or more advertisements from a plurality of labeled advertisements in a database that match the current advertising category of the first live content stream.

10. The non-transitory computer readable medium of claim 9 , wherein the first live content stream includes one or more advertising breaks in the first live content stream, and wherein the executed instructions cause the computing system to select the one or more advertisements in real-time for an upcoming advertisement break in the first live content stream.

11. A computer-implemented method of real-time content data processing, the method being performed by one or more processors and comprising:

storing, in a database, a plurality of data models, each data model being configured to sort datasets based on a set of criteria unique to the data model;

receiving a content policy from a content streaming platform on which a plurality of live content streams are provided simultaneously to a plurality of users, the content policy identifying a plurality of moderated content characteristics;

implementing, in real-time, a content moderation service for the content streaming platform that is based on the content policy, by:

processing the plurality of live content streams of the content streaming platform;

for each live content stream of the plurality of live content streams, (i) executing a multi-headed model that utilizes the plurality of data models to identify each content characteristic of the plurality of moderated content characteristics that is present in the live content stream; and (ii) generating a labeled content file describing each live content stream of the plurality of live content streams; and

for at least a first live content stream of the plurality of live content streams, automatically performing an action, without user input, in response to detecting that the first live content stream of the plurality of live content streams includes one or more of the plurality of moderated content characteristics;

wherein the automatically performed action comprises transmitting the labeled content file to a computing device of the content streaming platform.

12. The method of claim 11 , wherein the set of criteria unique to each data model corresponds to at least one of classifying or labeling elements in content data of each of the plurality of live content streams.

13. The method of claim 11 , wherein the automatically performed action comprises at least one of transmitting a notification to a computing device of the content streaming platform or transmitting a command to shut down the first live content stream.

14. The method of claim 11 , wherein the first live content stream of the plurality of live content streams includes advertisements, the method further comprising:

determining, based on executing each data model of the plurality of data models on the first live content stream, a current advertising category for the first live content stream; and

selecting, for presentation on the first live content stream, one or more advertisements from a plurality of labeled advertisements in a database that match the current advertising category of the first live content stream.

15. The computing system of claim 1 , wherein the content policy specifies a set of moderation categories identified by a content moderation model, and wherein detecting that the first live content stream violates the content policy comprises identifying content in a first moderation category within the first live content stream based on the labeled content file.

16. The computing system of claim 15 , wherein the executed instructions further cause the computing system to:

automatically perform, without user input, a second action in response to identifying content in a second moderation category, different from the first content moderation category, specified by the content policy within a second live content stream in the plurality of live content streams based on a second labeled content file generated for the second live content stream.

17. The non-transitory computer readable medium of claim 6 , wherein the content policy specifies a set of moderation categories identified by the content moderation model, and wherein detecting that the first live content stream violates the content policy comprises identifying content in a first moderation category within the first live content stream based on the labeled content file.

18. The non-transitory computer readable medium of claim 17 , wherein the executed instructions further cause the computing system to:

automatically perform, without user input, a second action in response to identifying content in a second moderation category, different from the first content moderation category, specified by the content policy within a second live content stream in the plurality of live content streams based on a second labeled content file generated for the second live content stream.

19. The method of claim 12 , wherein the content policy specifies a set of moderation categories identified by the content moderation model, and wherein detecting that the first live content stream violates the content policy comprises identifying content in a first moderation category within the first live content stream based on the labeled content file.

20. The method of claim 19 , further comprising:

automatically perform, without user input, a second action in response to identifying content in a second moderation category, different from the first content moderation category, specified by the content policy within a second live content stream in the plurality of live content streams based on a second labeled content file generated for the second live content stream.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 13, 2022
From: KARPMAN, DMITRIY; GUO, KEVIN; WEBER, RYAN
To: CASTLE GLOBAL, INC.
Reel/Frame 058652/0389 →
Continuity (2)
Provisional Application 63259901 · Nov 16, 2021
Provisional Application 63244655 · Sep 15, 2021
Cited By (1)
US 12,457,256