IP Library Granted Patent US 8,805,854
Granted Patent B2
US 8,805,854 · App. 12/489,861 · Granted Aug 12, 2014

Methods and apparatus for determining a mood profile associated with media data

View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 8,805,854
App. No.
12/489,861
Granted
Aug 12, 2014
Kind
B2
Abstract

In an embodiment, a method is provided for determining a mood profile of media data. In this method, mood is determined across multiple elements of mood for the media data to create a mood profile associated with the media data. In some embodiments, the mood profile is then used to determine congruencies between one or more pieces of media data.

Claims (206)

1. A method of identifying a congruency of media data, the method comprising:

accessing a first mood profile digest comprising a first vector including a first plurality of first mood categories, each having an associated value;

accessing a second mood profile digest comprising a second vector including a second plurality of second mood categories, each having an associated value;

determining that at least one first mood category is similar to at least one second mood category based on a correlates matrix that quantifies a similarity relationship between the first mood category and the second mood category,

the determining including calculation of a normalized comparison vector of the first mood profile digest in accordance with

A

comp

[

n

]

=

m

=

1

M

A

score

[

m

]

×

C

(

A

category

[

m

]

,

A

category

[

n

]

)

,

wherein A comp [n] is an n th element of the normalized comparison vector A comp , A score [m] is a score of an m th element of the first mood profile digest A, A category [m] is a first mood category of the m th element of the first mood profile digest A, and C(x,y) is a comparison value between the first and second mood categories x and y as indicated in the correlates matrix; and

dependent upon the similarity between the first mood category and the second mood category,

comparing the value associated with the first mood category with the value associated with the second mood category,

the comparing of the values being performed by a processor of a machine; and

generating a similarity score representing a degree of congruency between the first mood profile digest and the second mood profile digest based on the comparing of the associated values.

2. The method of claim 1 , wherein

the first mood profile digest is a portion of a first mood profile; and

the second mood profile digest is a portion of a second mood profile.

3. The method of claim 1 , wherein

the first mood profile digest is a summarization of a first mood profile; and

the second mood profile digest a summarization of a second mood profile.

4. The method of claim 1 further comprising:

comparing a further value associated with a further first mood category of the first plurality of first mood categories with a further value associated with a further second mood category of the second plurality of second mood categories; and wherein

the generating of the similarity score is based on the comparing of the further values.

5. The method of claim 1 , wherein

the correlates matrix contains a comparative value indicating an extent of similarity between the first mood category and the second mood category; and wherein

the comparing of the value associated with the first mood category with the value associated with the second mood category is based on the comparative value.

6. The method of claim 5 , further comprising:

generating a first set of normalized values based on the comparative value and based on values associated with the first plurality of first mood categories;

generating a second set of normalized values based on the comparative value and based on values associated with the second plurality of second mood categories; and wherein

the generating of the similarity score is based on the first set of normalized values and based on the second set of normalized values.

7. The method of claim 6 , further comprising

determining that the first mood category and the second mood category are different mood categories; and wherein

the generating of at least one of the first set of normalized values or the second set of normalized values is based on the determining that the first mood category in the second mood category are not the same.

8. The method of claim 6 , wherein

the first mood category is predominant among the first plurality of first mood categories, based on the value associated with the first mood category being largest within the first vector;

the second mood category is predominant among the second plurality of second mood categories, based on the value associated with the second mood category being largest within the second vector; and the method further comprises

identifying the comparative value within the correlates matrix based on the first and second mood categories being predominant.

9. The method of claim 1 , wherein:

the first mood profile digest is associated with a first recording;

the second mood profile digest is associated with a second recording; and the method further comprises

retrieving the second recording from a database based on the similarity score exceeding a threshold similarity.

10. The method of claim 1 , further comprising:

communicating an audio identifier to a server,

the audio identifier identifying an audio recording accessible by a media player;

receiving the first mood profile digest from the server,

the first mood profile digest identifying at least one mood associated with the audio recording; and

selecting the second mood profile digest from a set of mood profile digests received from the server.

11. A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:

accessing a first mood profile digest comprising a first vector including a first plurality of first mood categories, each having an associated value;

accessing a second mood profile digest comprising a second vector including a second plurality of second mood categories, each having an associated value;

determining that at least one first mood category is similar to at least one second mood category based on a correlates matrix that quantifies a similarity relationship between the first mood category and the second mood category,

the determining including calculation of a normalized comparison vector of the first mood profile digest in accordance with

A

comp

[

n

]

=

m

=

1

M

A

score

[

m

]

×

C

(

A

category

[

m

]

,

A

category

[

n

]

)

,

wherein A comp [n] is an n th element of the normalized comparison vector A comp , A score [m] is a score of an m th element of the first mood profile digest A, A category [m] is a first mood category of the m th element of the first mood profile digest A, and C(x,y) is a comparison value between the first and second mood categories x and y as indicated in the correlates matrix; and

dependent upon the similarity between the first mood category and the second mood category,

comparing the value associated with the first mood category with the value associated with the second mood category, the comparing of the values being performed by the one or more processors of the machine; and

generating a similarity score representing a degree of congruency between the first mood profile digest and the second mood profile digest based on the comparing of the associated values.

12. The non-transitory machine-readable storage medium of claim 11 , wherein:

the correlates matrix contains a comparative value indicating an extent of similarity between the first mood category and the second mood category; and wherein

the comparing of the value associated with the first mood category with the value associated with the second mood category is based on the comparative value.

13. The non-transitory machine-readable storage medium of claim 12 , wherein the operations further comprise:

generating a first set of normalized values based on the comparative value and based on values associated with the first plurality of first mood categories;

generating a second set of normalized values based on the comparative value and based on values associated with the second plurality of second mood categories; and wherein

the generating of the similarity score is based on the first set of normalized values and based on the second set of normalized values.

14. The non-transitory machine-readable storage medium of claim 13 , wherein the operations further comprise:

determining that the first mood category and the second mood category are different mood categories; and wherein

the generating of at least one of the first set of normalized values or the second set of normalized values is based on the determining that the first mood category in the second mood category are not the same.

15. The non-transitory machine-readable storage medium of claim 13 , wherein:

the first mood category is predominant among the first plurality of first mood categories, based on the value associated with the first mood category being largest within the first vector;

the second mood category is predominant among the second plurality of second mood categories, based on the value associated with the second mood category being largest within the second vector; and the operations further comprise

identifying the comparative value within the correlates matrix based on the first and second mood categories being predominant.

16. Apparatus comprising:

a mood determining module configured to:

access a first mood profile digest comprising a first vector including a first plurality of first mood categories, each having an associated value; and

access a second mood profile digest comprising a second vector including a second plurality of second mood categories, each having an associated value; and

a processor configured by a mood comparing module to:

determine that at least one first mood category is similar to at least one second mood category based on a correlates matrix that quantifies a similarity relationship between the first mood category and the second mood category,

the determining including calculation of a normalized comparison vector of the first mood profile digest in accordance with

A

comp

[

n

]

=

m

=

1

M

A

score

[

m

]

×

C

(

A

category

[

m

]

,

A

category

[

n

]

)

,

wherein A comp [n] is an n th element of the normalized comparison vector A comp, A score [m] is a score of an m th element of the first mood profile digest A, A category [m] is a first mood category of the m th element of the first mood profile digest A, and C(x,y) is a comparison value between the first and second mood categories x and y as indicated in the correlates matrix; and

dependent upon the similarity between the first mood category and the second mood category,

compare the value associated with the first mood category with the value associated with the second mood category; and

generate a similarity score representing a degree of congruency between the first mood profile digest and the second mood profile digest based on the comparing of the associated values.

17. The apparatus of claim 16 , wherein:

the correlates matrix contains a comparative value indicating an extent of similarity between the first mood category and the second mood category; and wherein

the mood comparing module configures the processor to compare the value associated with the first mood category with the value associated with the second mood category based on the comparative value.

18. The apparatus of claim 17 , wherein:

the mood comparing module configures the processor to:

generate a first set of normalized values based on the comparative value and based on values associated with the first plurality of first mood categories; and

generate a second set of normalized values based on the comparative value and based on values associated with the second plurality of second mood categories; and wherein

the generating of the similarity score is based on the first set of normalized values and based on the second set of normalized values.

19. The apparatus of claim 18 , wherein:

the mood comparing module configures the processor to determine that the first mood category and the second mood category are different mood categories; and

the generating of at least one of the first set of normalized values or the second set of normalized values is based on the determining that the first mood category in the second mood category are not the same.

20. The apparatus of claim 18 , wherein:

the first mood category is predominant among the first plurality of first mood categories, based on the value associated with the first mood category being largest within the first vector;

the second mood category is predominant among the second plurality of second mood categories, based on the value associated with the second mood category being largest within the second vector; and

the mood comparing module configures the processor to identify the comparative value within the correlates matrix based on the first and second mood categories being predominant.

Assignments (13)
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 →
RELEASE OF SECURITY INTEREST IN PATENT RIGHTS Recorded Feb 8, 2017
From: JPMORGAN CHASE BANK, N.A.
To: GRACENOTE, INC.; CASTTV INC.; TRIBUNE MEDIA SERVICES, LLC; TRIBUNE DIGITAL VENTURES, LLC
Reel/Frame 041656/0804 →
SECURITY AGREEMENT Recorded Nov 13, 2014
From: GRACENOTE, INC.; TRIBUNE BROADCASTING COMPANY, LLC; TRIBUNE DIGITAL VENTURES, LLC; TRIBUNE MEDIA COMPANY
To: JPMORGAN CHASE BANK, N.A., AS COLLATERAL AGENT
Reel/Frame 034231/0333 →
SECURITY INTEREST Recorded Mar 19, 2014
From: GRACENOTE, INC.
To: JPMORGAN CHASE BANK, N.A., AS COLLATERAL AGENT
Reel/Frame 032480/0272 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 17, 2009
From: CHEN, CHING-WEI; LEE, KYOGU; DIMARIA, PETER C.; CREMER, MARKUS K.
To: GRACENOTE, INC.
Reel/Frame 022977/0822 →