# US 12,120,390 B2 · Methods and apparatus to detect and rectify false set top box tuning data > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,120,390 B2 - Document ID: US12120390B2 - Status: Granted - Kind: B2 - Application number: 18/308,913 - Filed: 2023-04-28 - Published: 2023-09-14 - Granted: 2024-10-15 - Earliest claimed: 2017-11-21 - Assignees: The Nielsen Company (US), LLC - Applicants: The Nielsen Company (US), LLC - Inventors: Balachander Shankar; Jonathan Sullivan; Molly Poppie; John Charles Coughlin; Neung Soo Ha; Paul Chimenti; Rachel Worth Olson; Samantha M. Mowrer; David J. Kurzynski; Joshua Ivan Friedman; Adam E. Hasinski - Web page: https://patentgrep.com/patent/US12120390B2 ## CPC - H04N 21/44222: {Analytics of user selections, e.g. selection of programmes or purchase activity (monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33)} - H04N 21/251: {Learning process for intelligent management, e.g. learning user preferences for recommending movies (details of learning user preferences for the retrieval of video data in a video database G06F16/739; computer systems using learning methods G06N3/08)} - H04N 21/25833: {involving client hardware characteristics, e.g. manufacturer, processing or storage capabilities (allocation of resources considering hardware capabilities in multiprogramming arrangements G06F9/5044; allocation of resources considering software capabilities in multiprogramming arrangements G06F9/5055)} - H04N 21/6582: {Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number (arrangements where receivers interact with the broadcast H04H20/38)} - H04N 21/84: Generation or processing of descriptive data, e.g. content descriptors {(systems specially adapted for using meta-information in broadcast systems H04H60/73)} - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying, by executing an instruction with a processor, in the return path data, first tuning data corresponding to a first group of set top boxes, the first group of set top boxes classified as associated with machine events, determining, by executing an instruction with a processor, a ratio between first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set top boxes, the second tuning events attributed to a second group of the set top boxes classified at not associated with machine events, and in response to the ratio satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data. ## Claims ### Claim 1 A computing system comprising: a processor; at least one memory, having stored thereon program instructions that, upon execution by the processor, cause performance of operations comprising: identifying, in return path data, first tuning data corresponding to a first group of set-top boxes, the first group of set-top boxes classified as associated with machine events; making a comparison of first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set-top boxes, the second tuning events attributed to a second group of the set-top boxes; and based on an output of the comparison satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data. ### Claim 2 (depends on 1) The computing system of claim 1, wherein the second group of the set-top boxes have a different classification than the first group of set-top boxes. ### Claim 3 (depends on 1) The computing system of claim 1, wherein the second group of the set-top boxes are classified as not likely to exhibit machine events. ### Claim 4 (depends on 1) The computing system of claim 1, wherein the removed second tuning data includes one or more of false tuning data or veridical tuning data contained in the return path data. ### Claim 5 (depends on 1) The computing system of claim 1, the operations further comprising: identifying the second tuning data associated with the time interval based on a portion of the first tuning data defining a pattern indicative of an occurrence of at least one of the machine events associated with the first group of set-top boxes. ### Claim 6 (depends on 5) The computing system of claim 5, wherein the time interval is longer than a duration of the at least one of the machine events. ### Claim 7 (depends on 5) The computing system of claim 5, wherein the at least one of the machine events corresponds to at least one phantom tuning machine event. ### Claim 8 A method to process return path data from set-top boxes, the method comprising: identifying, by executing an instruction with a processor, in the return path data, first tuning data corresponding to a first group of set-top boxes, the first group of set-top boxes classified as associated with machine events; making, by executing an instruction with the processor, a comparison of first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set-top boxes, the second tuning events attributed to a second group of the set-top boxes; and based on an output of the comparison satisfying a threshold during a time interval, removing, by executing an instruction with the processor, second tuning data associated with the time interval from the first tuning data. ### Claim 9 (depends on 8) The method of claim 8, wherein the second tuning data has a smaller data size than the first tuning data. ### Claim 10 (depends on 8) The method of claim 8, wherein the threshold varies across different periods of time. ### Claim 11 (depends on 8) The method of claim 8, wherein the removed second tuning data includes one or more of false tuning data or veridical tuning data contained in the return path data. ### Claim 12 (depends on 8) The method of claim 8, further comprising identifying the second tuning data associated with the time interval based on a portion of the first tuning data defining a pattern indicative of an occurrence of at least one of the machine events associated with the first group of set-top boxes. ### Claim 13 (depends on 12) The method of claim 12, wherein the time interval is longer than a duration of the at least one of the machine events. ### Claim 14 (depends on 12) The method of claim 12, wherein the at least one of the machine events corresponds to at least one phantom tuning machine events. ### Claim 15 A non-transitory computer-readable medium comprising computer-readable instructions which, when executed by a processor, cause the processor to perform operations comprising: identifying, in return path data, first tuning data corresponding to a first group of set-top boxes, the first group of set-top boxes classified as associated with machine events; making a comparison of first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of set-top boxes, the second tuning events attributed to a second group of the set-top boxes; and based on an output of the comparison satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data. ### Claim 16 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein the second tuning data has a smaller data size than the first tuning data. ### Claim 17 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein the threshold is to vary across different periods of time. ### Claim 18 (depends on 15) The non-transitory computer-readable medium of claim 15, wherein the removed second tuning data includes one or more of false tuning data or veridical tuning data contained in the return path data. ### Claim 19 (depends on 15) The non-transitory computer-readable medium of claim 15, the operations further comprising: identifying the second tuning data associated with the time interval based on a portion of the first tuning data defining a pattern indicative of an occurrence of at least one of the machine events associated with the first group of set-top boxes. ### Claim 20 (depends on 19) The non-transitory computer-readable medium of claim 19, wherein the at least one of the machine events corresponds to at least one phantom tuning machine event.