Methods and apparatus to generate audience metrics using matrix analysis

Patent metadata

Field	Value
Publication number	US-12450620-B2
Application number	US-202418655508-A
Country	US
Kind code	B2
Filing date	May 6, 2024
Priority date	Aug 21, 2020
Publication date	Oct 21, 2025
Grant date	Oct 21, 2025

Abstract

An example apparatus includes audience metrics collecting circuitry to access first audience metrics from a server, and access second audience metrics from the server, matrix building circuitry to build a matrix of the first audience metrics and the second audience metrics, missing values of the matrix corresponding to the second audience metrics, data transforming circuitry to transform the first audience metrics and the second audience metrics in the matrix, missing value calculating circuitry to determine imputed transformed values of the missing values using a recommender system, and the data transforming circuitry to recover imputed values of the missing values based on the imputed transformed values.

First claim

What is claimed is:

1. An audience measurement system comprising:
a panel monitor server configured to:
receive network communications identifying media items presented at client devices of panelists of an audience measurement entity, wherein the media items are tagged with beacon instructions that are downloaded to the client devices when the client devices access the media items, wherein the beacon instructions cause the client devices to transmit the network communications to the panel monitor server,
based on the network communications received from the client devices in accordance with the beacon instructions, log demographic impressions of the media items in association with known demographic data for the panelists, and
generate panelist audience metrics based on the demographic impressions;

a computing system comprising at least one processor and a memory, the computing system configured to:
access the panelist audience metrics from the panel monitor server,
access, from a census monitor server, census audience metrics generated based on census impressions of the media items logged by the census monitor server,
determine an audience metrics matrix of the panelist audience metrics and the census audience metrics, categorized by two or more of audience size for the media items, impression count for the media items, or duration of the media items, wherein the audience metrics matrix comprises missing audience metrics values for a portion of demographic groups and for a portion of the media items, and wherein the audience metrics matrix comprises computer-generated audience metrics data bias represented by the missing audience metrics values,
apply a recommender system to the audience metrics matrix to predict audience metrics values corresponding to the missing audience metrics values, wherein the recommender system predicts the audience metrics values for the audience metrics matrix using a user-item matrix different from the audience metrics matrix, wherein the user-item matrix comprises values representing ratings assigned to particular media items by users that accessed the particular media items, and wherein the predicted audience metrics are differ from user-assigned ratings of media items, and
based on the predicted audience metrics values, transmit audience metrics data to the panel monitor server and the census monitor server to cause the panel monitor server and the census monitor server to update respective audience metrics databases.

2. The audience measurement system of claim 1 , wherein the recommender system is configured to predict user preference for media items.

3. The audience measurement system of claim 1 , wherein the recommender system uses sparse matrix factorization.

4. The audience measurement system of claim 1 , wherein the recommender system comprises a deep factorization machine.

5. The audience measurement system of claim 1 , wherein demographic data for users that accessed the media items was not logged by the census monitor server in association with the census impressions.

6. The audience measurement system of claim 1 , wherein the recommender system comprises a multilayer neural network.

7. The audience measurement system of claim 1 , wherein the media items are streaming media items.

8. The audience measurement system of claim 1 , further comprising the census monitor server.

9. A non-transitory computer readable storage medium comprising instructions that, when executed, cause at least one processor to perform operations comprising:
receiving, at a panel monitor server, network communications identifying media items presented at client devices of panelists of an audience measurement entity, wherein the media items are tagged with beacon instructions that are downloaded to the client devices when the client devices access the media items, wherein the beacon instructions cause the client devices to transmit the network communications to the panel monitor server;
based on the network communications received from the client devices in accordance with the beacon instructions, logging demographic impressions of the media items in association with known demographic data for the panelists;
generating panelist audience metrics based on the demographic impressions;
accessing the panelist audience metrics from the panel monitor server;
accessing, from a census monitor server, census audience metrics generated based on census impressions of the media items logged by the census monitor server;
determining an audience metrics matrix of the panelist audience metrics and the census audience metrics, categorized by two or more of audience size for the media items, impression count for the media items, or duration of the media items, wherein the audience metrics matrix comprises missing audience metrics values for a portion of demographic groups and for a portion of the media items, and wherein the audience metrics matrix comprises computer-generated audience metrics data bias represented by the missing audience metrics values,
applying a recommender system to the audience metrics matrix to predict audience metrics values corresponding to the missing audience metrics values, wherein the recommender system predicts the audience metrics values for the audience metrics matrix using a user-item matrix different from the audience metrics matrix, wherein the user-item matrix comprises values representing ratings assigned to particular media items by users that accessed the particular media items, and wherein the predicted audience metrics are different from user-assigned ratings of media items; and
based on the predicted audience metrics values, transmitting audience metrics data to the panel monitor server and the census monitor server to cause the panel monitor server and the census monitor server to update respective audience metrics databases.

10. The non-transitory computer readable storage medium of claim 9 , wherein the recommender system is configured to predict user preference for media items.

11. The non-transitory computer readable storage medium of claim 9 , wherein the recommender system uses sparse matrix factorization.

12. The non-transitory computer readable storage medium of claim 9 , wherein the recommender system comprises a deep factorization machine.

13. The non-transitory computer readable storage medium of claim 9 , wherein demographic data for users that accessed the media items was not logged by the census monitor server in association with the census impressions.

14. The non-transitory computer readable storage medium of claim 9 , wherein the recommender system comprises a multilayer neural network.

15. The non-transitory computer readable storage medium of claim 9 , wherein the media items are streaming media items.

16. A method comprising:
receiving, at a panel monitor server, network communications identifying media items presented at client devices of panelists of an audience measurement entity, wherein the media items are tagged with beacon instructions that are downloaded to the client devices when the client devices access the media items, wherein the beacon instructions cause the client devices to transmit the network communications to the panel monitor server;
based on the network communications received from the client devices in accordance with the beacon instructions, logging demographic impressions of the media items in association with known demographic data for the panelists;
generating panelist audience metrics based on the demographic impressions;
accessing the panelist audience metrics from the panel monitor server;
acces

Assignees

• Nielsen Co Us Llc

Inventors

• Cui Dongbo
• Murphy Edward
• Sheppard Michael Richard
• Forteguerre David
• White Jessica Lynn
• Yi Pengfei
• Sullivan Jonathan

Classifications

• G06F18/10

  Pre-processing; Data cleansing · CPC title

• G06F17/16

  Matrix or vector computation {, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization (matrix transposition G06F7/78)} · CPC title

• G06V10/764

  using classification, e.g. of video objects · CPC title

• G06Q30/0201 Primary

  Market modelling; Market analysis; Collecting market data · CPC title