US 12,008,587 B2
Methods and apparatus to generate audience metrics using matrix analysis
DongBo Cui, New York, NY (US); Edward Murphy, Uncasville, CT (US); Michael Richard Sheppard, Holland, MI (US); David Forteguerre, Brooklyn, NY (US); Jessica Lynn White, Plant City, FL (US); PengFei Yi, Shanghi (CN); and Jonathan Sullivan, Hurricane, UT (US)
Assigned to The Nielsen Company (US), LLC, New York, NY (US)
Filed by The Nielsen Company (US), LLC, New York, NY (US)
Filed on Aug. 19, 2021, as Appl. No. 17/406,878.
Claims priority of provisional application 63/106,242, filed on Oct. 27, 2020.
Claims priority of provisional application 63/068,831, filed on Aug. 21, 2020.
Prior Publication US 2022/0058663 A1, Feb. 24, 2022
Int. Cl. G06Q 30/0201 (2023.01); G06F 17/16 (2006.01); G06F 18/10 (2023.01)
CPC G06Q 30/0201 (2013.01) [G06F 17/16 (2013.01); G06F 18/10 (2023.01)] 20 Claims
OG exemplary drawing
 
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, the beacon instructions to 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 on 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, wherein demographic data for users that accessed the media items was not logged by the census monitor server in association with the census impressions,
build a sparse matrix of the panelist audience metrics and the census audience metrics, wherein the sparse matrix comprises missing audience metrics values for a portion of demographic groups and for a portion of the media items, and wherein the sparse matrix comprises computer-generated audience metrics data bias represented by the missing audience metrics values,
normalize the panelist audience metrics and the census audience metrics in the sparse matrix to generate a sparse transformed matrix,
apply a recommender model to the sparse transformed matrix to predict audience metrics values corresponding to the missing audience metrics,
generate a supplemented transformed matrix comprising the predicted audience metrics values and audience metrics values from the sparse transformed matrix,
perform reverse transformations of the supplemented transformed matrix to generate a completed audience metrics matrix, and
transmit audience 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.