IP Library Granted Patent US 11,762,898
Granted Patent B1
US 11,762,898 · App. 17/657,572 · Granted Sep 19, 2023

Generating and utilizing digital media clips based on contextual metadata from digital environments

Inventors: Arunsunai Anbukarasi Anbalagapandian (San Francisco, CA); Devin Mancuso (Alameda, CA); Rituparna Vincent (Alamo, CA); Viksit Gaur (San Francisco, CA)
Assignee: Dropbox, Inc.
G06F16/435G06F16/44G06F16/45
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Quick Facts
Patent No.
US 11,762,898
App. No.
17/657,572
Granted
Sep 19, 2023
Kind
B1
Abstract

The present disclosure relates to systems, methods, and non-transitory computer-readable media that dynamically capture, organize, and utilize digital media clips. For example, in one or more implementations, the disclosed systems can capture and generate digital media clips of content items that include both content metadata of the content items as well as contextual metadata of contextual signals surrounding the content item. Additionally, in some implementations, the disclosed systems analyze contextual metadata to search, retrieve, discover, and organize new and existing digital media clips. Further, in various implementations, the disclosed systems facilitate generating digital media clip libraries as well as the creation of digital media collections, where different types of digital media clips can be combined in a cohesive interactive graphical user interface.

Claims (69)

1. A computer-implemented method comprising:

maintaining, for a user account of a content management system, a media clip library comprising digital media clips each having a content item, content metadata, and contextual metadata;

detecting a content item not associated with the user account;

determining a correlation between the content item and one or more digital media clips within the media clip library; and

based on the correlation, adding a new digital media clip to the media clip library by generating the new digital media clip from the content item.

2. The computer-implemented method of claim 1 , further comprising determining a correlation between the content item and the one or more digital media clips of the media clip library by comparing the content item with contextual metadata of digital media clips within the media clip library.

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

providing a recommendation to generate a digital media clip of the content item; and

based on generating the digital media clip of the content item, adding the digital media clip to the media clip library of the user account.

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

identifying a plurality of content items not associated with the user account;

selecting the content item from the plurality of content items by comparing the plurality of content items with contextual metadata of digital media clips within the media clip library; and

providing a suggestion to add the content item to the media clip library as a digital media clip.

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

determining, for a digital media clip in the media clip library of the user account, that a copy of the digital media clip is located in a second media clip library of a second user account of the content management system;

determining an additional correlation between an additional digital media clip in the second media clip library of the second user account and the digital media clip in the media clip library of the user account; and

based on the additional correlation, providing a content item from the additional digital media clip within the second media clip library of the second user account to the user account as the content item.

6. The computer-implemented method of claim 1 , further comprising generating a digital media clip of the content item by:

capturing the content item;

extracting content metadata from the content item; and

generating contextual metadata from contextual signals corresponding to one or more digital environments in which the content item currently resides.

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

based on a search query, identifying a plurality of content items not associated with the user account;

determining one or more implicit user preferences based on contextual metadata of digital media clips in the media clip library;

filtering out the plurality of content items based on the one or more implicit user preferences to identify a subset of content items; and

providing the subset of content items in response to the search query.

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

identifying a target digital media clip;

receiving user input indicating a relatedness level ranging from highly correlated to uncorrelated;

tuning parameters of a media clip classification machine-learning model based on the relatedness level; and

identifying one or more content items utilizing the tuned media clip classification machine-learning model and the target digital media clip.

9. A non-transitory computer-readable storage medium comprising instructions that, when executed by at least one processor, cause a computer device to:

maintain, for a user account of a content management system, a media clip library comprising digital media clips each having a content item, content metadata, and contextual metadata;

detect a content item not associated with the user account;

determine correlation scores between the content item and one or more digital media clips within the media clip library;

based on the correlation scores, provide a recommendation to generate a digital media clip of the content item for the media clip library; and

based on receiving user confirmation of the recommendation, generate a digital media clip of the content item.

10. The non-transitory computer-readable storage medium of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the computer device to:

identify a plurality of content items not associated with the user account comprising the content item; and

select the content item from the plurality of content items based on the correlation scores.

11. The non-transitory computer-readable storage medium of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the computer device to add the digital media clip to the media clip library of the user account.

12. The non-transitory computer-readable storage medium of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the computer device to:

determine a correlation between contextual metadata of the digital media clip and contextual metadata from a second media clip library of a second user account of the content management system; and

based on the correlation, provide an additional recommendation to the second user account to add the digital media clip to a second media clip library associated with the second user account.

13. The non-transitory computer-readable storage medium of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the computer device to determine the correlation scores between the content item and the one or more digital media clips of the media clip library by comparing contextual metadata related to the content item with contextual metadata of digital media clips within the media clip library.

14. The non-transitory computer-readable storage medium of claim 9 , further comprising instructions that, when executed by the at least one processor, cause the computer device to select the content item based on a correlation score for the content item satisfying a digital media clip suggestion threshold.

15. A system comprising:

at least one processor; and

a non-transitory computer memory comprising instructions that, when executed by the at least one processor, cause the system to:

maintain, for a user account of a content management system, a media clip library comprising digital media clips each having a content item, content metadata, and contextual metadata;

identify a plurality of content items not associated with the user account;

determine one or more content items from the plurality of content items by comparing the plurality of content items with contextual metadata of one or more digital media clips within the media clip library; and

add one or more digital media clips to the media clip library by generating one or more digital media clips from the one or more content items that correlate to the contextual metadata of one or more digital media clips within the media clip library.

16. The system of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to provide one or more recommendations to generate the one or more digital media clips of the one or more content items.

17. The system of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to identify the plurality of content items from an additional media clip library of an additional user of the content management system.

18. The system of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to:

identify a set of content items not associated with the user account based on a search query;

determine one or more implicit user preferences based on contextual metadata of digital media clips in the media clip library;

filter out the set of content items based on the one or more implicit user preferences to identify a subset of content items; and

provide the subset of content items in response to the search query.

19. The system of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to:

identify a target digital media clip;

receive user input indicating a relatedness level ranging from highly correlated to uncorrelated;

tune parameters of a media clip classification machine-learning model based on the relatedness level; and

identify a set of content items utilizing the tuned media clip classification machine-learning model and the target digital media clip.

20. The system of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the system to generate a digital media clip of the content item by:

capturing the content item from a digital environment;

extracting content metadata from the content item; and

generating contextual metadata from contextual signals detected from the digital environment.

Assignments (2)
SECURITY INTEREST Recorded Dec 12, 2024
From: DROPBOX, INC.
To: WILMINGTON TRUST, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
Reel/Frame 069604/0611 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 15, 2022
From: ANBALAGAPANDIAN, ARUNSUNAI ANBUKARASI; MANCUSO, DEVIN; VINCENT, RITUPARNA; GAUR, VIKSIT
To: DROPBOX, INC.
Reel/Frame 059609/0472 →