US 12,445,685 B2
Methods and apparatus to impute media consumption behavior
David J. Kurzynski, South Elgin, IL (US); Balachander Shankar, Tampa, FL (US); Richard Peters, Gurnee, IL (US); Jonathan Sullivan, Hurricane, UT (US); and Molly Poppie, Arlington Heights, IL (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 Jun. 20, 2024, as Appl. No. 18/748,794.
Application 18/748,794 is a continuation of application No. 17/986,571, filed on Nov. 14, 2022, granted, now 12,058,416.
Application 17/986,571 is a continuation of application No. 17/164,506, filed on Feb. 1, 2021, granted, now 11,503,370, issued on Nov. 15, 2022.
Application 17/164,506 is a continuation of application No. 16/773,725, filed on Jan. 27, 2020, granted, now 10,911,828, issued on Feb. 2, 2021.
Application 16/773,725 is a continuation of application No. 15/361,314, filed on Nov. 25, 2016, granted, now 10,547,906, issued on Jan. 28, 2020.
Claims priority of application No. 201611019573 (IN), filed on Jun. 7, 2016.
Prior Publication US 2024/0340497 A1, Oct. 10, 2024
Int. Cl. H04N 21/466 (2011.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 30/0251 (2023.01); H04N 21/442 (2011.01); H04N 21/45 (2011.01); H04N 21/84 (2011.01)
CPC H04N 21/4667 (2013.01) [G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06Q 30/0255 (2013.01); H04N 21/44224 (2020.08); H04N 21/4532 (2013.01); H04N 21/84 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An audience measurement computing system for performing viewership assignment, the audience measurement computing system comprising:
a network interface;
a processor; and
memory having stored thereon machine-readable instructions that, when executed by the processor, cause performance of operations comprising:
obtaining, via the network interface and from media meters in a first area, first tuning data associated with first panelists exposed to first media, wherein the media meters correspond to first households, and wherein the media meters do not identify, within the first tuning data, respective ones of the first panelists that are exposed to the first media;
classifying a subset of the first tuning data as heavy tuning data based on one or more of a total number of the first households or a total number of exposure minutes of the first media;
determining that the heavy tuning data represents a local bias in the first area based on a comparison of exposure minutes of second media viewed by second panelists in a second area to exposure minutes of the second media viewed by third panelists in the first area, wherein the second media is related to the first media;
obtaining, via the network interface and from people meters in the second area, viewing data associated with the second panelists, wherein the people meters identify, within the viewing data, respective ones of the second panelists that are exposed to the second media; and
based on determining that the heavy tuning data represents the local bias, imputing the viewing data associated with the second panelists to at least one of the first panelists.