IP Library Granted Patent US 10,546,016
Granted Patent B1
US 10,546,016 · App. 15/343,884 · Granted Jan 28, 2020

Audiovisual content curation system

Inventors: Peter C. DiMaria (Berkeley, CA); Andrew Silverman (Berkeley, CA)
Assignee: Gracenote, Inc.
G06F16/61G06F16/686
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Quick Facts
Patent No.
US 10,546,016
App. No.
15/343,884
Granted
Jan 28, 2020
Kind
B1
Abstract

Systems and methods are provided for filtering at least one media content catalog based on criteria for a station library to generate a first list of candidate tracks for the station library, combining a similarity score and a popularity score for each track of the first list of candidate tracks to generate a total score for each track of the first list of candidate tracks, generating a list of top ranked tracks for the first genre, and returning the list of top ranked tracks of the first genre as part of the station library.

Claims (64)

1. A method, comprising:

receiving, at a server computer, a request for a station library, the request including criteria for the station library, the criteria including at least a first genre;

filtering, by the server computer, at least one media content catalog based on the criteria for the station library to generate a first list of candidate tracks for the station library;

determining, by the server computer, a first total number of tracks to be selected for the first genre based on the criteria;

generating, by the server computer, first similarity scores for respective ones of the tracks of the first list of candidate tracks in a first step, the first step including generating the first similarity scores determining correlation values between a primary genre for respective ones of the tracks in the first list of candidate tracks and the first genre, wherein the correlation values are compared to a specified threshold;

determining, by the server computer, first popularity scores for respective ones of the tracks of the first list of candidate tracks;

combining, by the server computer, the first similarity score and the first popularity score associated with each track of the first list of candidate tracks to generate first total scores for respective ones of the tracks of the first list of candidate tracks;

selecting, by the server computer, first top ranked tracks of the first list of candidate tracks based on the first total scores associated with respective ones of the tracks of the first list of candidate tracks and the first total number of tracks to be selected for the first genre to generate a list of top ranked tracks for the first genre; and

returning, by the server computer, the first list of top ranked tracks of the first genre as part of the station library.

2. The method of claim 1 , wherein the criteria include a second genre and wherein the method further includes:

filtering the at least one media content catalog based on the criteria for the station library to generate a second list of candidate tracks for the station library;

determining a second total number of tracks to be selected for the second genre based on the criteria;

generating second similarity scores for respective tracks of the second list of candidate tracks;

determining second popularity scores for respective tracks of the second list of candidate tracks;

combining the second similarity score and the second popularity score associated with each track of the second list of candidate tracks to generate second total scores for respective ones of the tracks of the second list of candidate tracks;

ranking the second list of candidate tracks based on the second total scores for respective tracks of the second list of candidate tracks;

selecting second top ranked tracks of the second list of candidate tracks based on the second total number of tracks to be selected for the second genre to generate a second list of top ranked tracks for the second genre; and

returning the second list of second top ranked tracks of the second genre as part of the station library.

3. The method of claim 2 , further including combining the first list of top ranked tracks for the first genre and the second list of top ranked tracks for the second genre into the station library.

4. The method of claim 3 , wherein the station library is sorted based on at least one of the first total score or the second total score associated with each track in the station library.

5. The method of claim 1 , wherein the station library includes a list of audio tracks and at least one descriptor including at least one of a rank, a title, an artist, an artist type, an album, a genre, a mood, an era, an origin, a popularity score, a similarity score, a total score, a catalogue identifier, or an external identifier.

6. The method of claim 1 , wherein the criteria for the station library include at least one of a genre, a mood, an era, an origin, an artist type, an artist profile, a catalogue identifier, or a percent mix.

7. The method of claim 1 , wherein generating the similarity scores for respective ones of the tracks in the first list of candidate tracks includes comparing the criteria of the request and qualities associated with each track.

8. The method of claim 1 , wherein a second step in generating the first similarity scores for respective ones of the tracks in the first list of candidate tracks includes

weighting the first similarity scores based on at least a genre vector, the similarity scores derived using an iterative process, the iterative process to add a common weight of the correlation to an allocated weight sum until all weights in the genre vector are allocated.

9. The method of claim 1 , wherein the criteria include a percent mix for the first genre, and wherein determining the first total number of tracks to be selected for the first genre is based on at least one of a percent mix or a predetermined total number of tracks for a station library.

10. The method of claim 1 , further including ranking the tracks of the first list of candidate tracks based on the total score associated with each track.

11. A server computer, comprising:

a processor; and

a non-transitory machine-readable medium including instructions that, when executed, cause the processor to at least:

receiving a request for a station library, the request including criteria for the station library, the criteria including at least a first genre;

filter at least one media content catalog based on the criteria for the station library to generate a first list of candidate tracks for the station library;

determining a first total number of tracks to be selected for the first genre based on the criteria;

generating first similarity scores for respective ones of the tracks of the first list of candidate tracks in a first step, the first step including generating the first similarity scores determining correlation values between a primary genre for resDective ones of the tracks in the first list of candidate tracks and the first genre, wherein the correlation values are compared to a specified threshold;

determining first popularity scores for respective ones of the tracks of the first list of candidate tracks;

combing the first similarity scores and the first popularity scores associated with each track of the first list of candidate tracks to generate first total scores for respective ones of the tracks of the first list of candidate tracks;

select first top ranked tracks of the first list of candidate tracks based on the first total scores associated with respective ones of the tracks of the first list of candidate tracks and the first total number of tracks to be selected for the first genre to generate a list of top ranked tracks for the first genre; and

return the first list of top ranked tracks of the first genre as part of the station library.

12. The server computer of claim 11 , wherein the criteria include a second genre, and wherein the instructions, when executed, cause the processor to perform operations further including:

filtering the at least one media content catalog based on the criteria for the station library to generate a second list of candidate tracks for the station library;

determining a second total number of tracks to be selected for the second genre based on the criteria;

generating second similarity scores for each track of the second list of candidate tracks;

determining second popularity scores for respective tracks of the second list of candidate tracks;

combining the second similarity scores and the second popularity scores for respective tracks of the second list of candidate tracks to generate second total scores for respective ones of the tracks of the second list of candidate tracks;

ranking the second list of candidate tracks based on the second total scores for respective tracks of the second list of candidate tracks;

selecting second top ranked tracks of the second list of candidate tracks based on the second total number of tracks to be selected for the second genre to generate a second list of top ranked tracks for the second genre; and

returning the second list of top ranked tracks of the second genre as part of the station library.

13. The server computer of claim 12 , wherein the instructions, when executed, cause the processor to perform operations further including: combining the first list of top ranked tracks for the first genre and the second list of top ranked tracks for the second genre into the station library.

14. The server computer of claim 13 , wherein the station library is sorted based on at least one of the first total score or the second total score associated with each track in the station library.

15. The server computer of claim 11 , wherein the station library includes a list of audio tracks and at least one descriptor including at least one of a rank, a title, an artist, an artist type, an album, a genre, a mood, an era, an origin, a popularity score, a similarity score, a total score, a catalogue identifier, or an external identifier.

16. The server computer of claim 11 , wherein the criteria for the station library includes at least one of a genre, a mood, an era, an origin, an artist type, an artist profile, a catalogue identifier, or a percent mix.

17. The server computer of claim 11 , wherein generating the similarity scores for respective ones of the tracks in the first list of candidate tracks includes comparing the criteria of the request against qualities associated with each track.

18. The server computer of claim 11 , wherein a second step in generating the first similarity scores for respective ones of the tracks in the first list of candidate tracks includes

weighting the first similarity scores based on at least a genre vector, the similarity scores derived using an iterative process, the iterative process to add a common weight of the correlation to an allocated weight sum until all weights in the genre vector are allocated.

19. The server computer of claim 11 , wherein the criteria include a percent mix for the first genre, and wherein determining the first total number of tracks to be selected for the first genre is based on at least one of a percent mix or a predetermined total number of tracks for a station library.

20. A non-transitory computer-readable medium comprising instructions stored thereon that, when executed by at least one processor, cause the at least one processor to perform operations including:

receiving a request for a station library, the request comprising criteria for the station library, the criteria including at least a first genre;

filtering at least one media content catalog based on the criteria for the station library to generate a first list of candidate tracks for the station library;

determining a total number of tracks to be selected for the first genre based on the criteria;

generating a similarity score for each track of the first list of candidate tracks in a first step, the first step including generating the first similarity scores determining correlation values between a primary genre for respective ones of the tracks in the first list of candidate tracks and the first genre, wherein the correlation values are compared to a specified threshold;

determining a popularity score for each track of the first list of candidate tracks;

combining the similarity score and the popularity score for each track of the first list of candidate tracks to generate a total score for each track of the first list of candidate tracks;

selecting top ranked tracks of the first list of candidate tracks based on the total number of tracks to be selected for the first genre to generate a list of top ranked tracks for the first genre; and

returning the list of top ranked tracks of the first genre as part of the station library.

Assignments (10)
RELEASE (REEL 054066 / FRAME 0064) Recorded May 11, 2023
From: CITIBANK, N.A.
To: A. C. NIELSEN COMPANY, LLC; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE MEDIA SERVICES, LLC; THE NIELSEN COMPANY (US), LLC; NETRATINGS, LLC
Reel/Frame 063605/0001 →
RELEASE (REEL 053473 / FRAME 0001) Recorded May 11, 2023
From: CITIBANK, N.A.
To: A. C. NIELSEN COMPANY, LLC; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE MEDIA SERVICES, LLC; THE NIELSEN COMPANY (US), LLC; NETRATINGS, LLC
Reel/Frame 063603/0001 →
SECURITY INTEREST Recorded May 8, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: ARES CAPITAL CORPORATION
Reel/Frame 063574/0632 →
SECURITY INTEREST Recorded Apr 28, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: CITIBANK, N.A.
Reel/Frame 063561/0381 →
SECURITY AGREEMENT Recorded Jan 31, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: BANK OF AMERICA, N.A.
Reel/Frame 063560/0547 →
RELEASE (REEL 042262 / FRAME 0601) Recorded Oct 13, 2022
From: CITIBANK, N.A.
To: GRACENOTE, INC.; GRACENOTE DIGITAL VENTURES, LLC
Reel/Frame 061748/0001 →
CORRECTIVE ASSIGNMENT TO CORRECT THE PATENTS LISTED ON SCHEDULE 1 RECORDED ON 6-9-2020 PREVIOUSLY RECORDED ON REEL 053473 FRAME 0001. ASSIGNOR(S) HEREBY CONFIRMS THE SUPPLEMENTAL IP SECURITY AGREEMENT. Recorded Oct 7, 2020
From: A.C. NIELSEN (ARGENTINA) S.A.; A.C. NIELSEN COMPANY, LLC; ACN HOLDINGS INC.; ACNIELSEN CORPORATION; ACNIELSEN ERATINGS.COM; AFFINNOVA, INC.; ART HOLDING, L.L.C.; ATHENIAN LEASING CORPORATION; CZT/ACN TRADEMARKS, L.L.C.; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; NETRATINGS, LLC; NIELSEN AUDIO, INC.; NIELSEN CONSUMER INSIGHTS, INC.; NIELSEN CONSUMER NEUROSCIENCE, INC.; NIELSEN FINANCE CO.; NIELSEN FINANCE LLC; NIELSEN INTERNATIONAL HOLDINGS, INC.; NIELSEN MOBILE, LLC; NMR INVESTING I, INC.; TCG DIVESTITURE INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC; VIZU CORPORATION; VNU MARKETING INFORMATION, INC.; NMR LICENSING ASSOCIATES, L.P.; NIELSEN HOLDING AND FINANCE B.V.; THE NIELSEN COMPANY B.V.; VNU INTERNATIONAL B.V.
To: CITIBANK, N.A
Reel/Frame 054066/0064 →
SUPPLEMENTAL SECURITY AGREEMENT Recorded Jun 9, 2020
From: A. C. NIELSEN COMPANY, LLC; ACN HOLDINGS INC.; ACNIELSEN CORPORATION; ACNIELSEN ERATINGS.COM; AFFINNOVA, INC.; ART HOLDING, L.L.C.; ATHENIAN LEASING CORPORATION; CZT/ACN TRADEMARKS, L.L.C.; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; NETRATINGS, LLC; NIELSEN AUDIO, INC.; NIELSEN CONSUMER INSIGHTS, INC.; NIELSEN CONSUMER NEUROSCIENCE, INC.; NIELSEN FINANCE CO.; NIELSEN FINANCE LLC; NIELSEN INTERNATIONAL HOLDINGS, INC.; NIELSEN MOBILE, LLC; NIELSEN UK FINANCE I, LLC; NMR INVESTING I, INC.; TCG DIVESTITURE INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC; VIZU CORPORATION; VNU MARKETING INFORMATION, INC.; NMR LICENSING ASSOCIATES, L.P.; NIELSEN HOLDING AND FINANCE B.V.; THE NIELSEN COMPANY B.V.; VNU INTERNATIONAL B.V.
To: CITIBANK, N.A.
Reel/Frame 053473/0001 →
SUPPLEMENTAL SECURITY AGREEMENT Recorded Apr 13, 2017
From: GRACENOTE, INC.; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE DIGITAL VENTURES, LLC
To: CITIBANK, N.A., AS COLLATERAL AGENT
Reel/Frame 042262/0601 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 15, 2016
From: DIMARIA, PETER C.; SILVERMAN, ANDREW
To: GRACENOTE, INC.
Reel/Frame 040316/0985 →
Continuity (1)
Provisional Application 62251952 · Nov 6, 2015