The Nielsen Comapny (US), LLC

Demetrios Fassois

David J Kurzynski

Michael Grotelueschen

Michael Evan Anderson

Fatemehossadat Miri

Tushar Chandra

Samantha M Mowrer

Jean Guerrettaz

Vince Tambellini

An example apparatus to perform media device on/off detection using return path data includes interface circuitry, machine readable instructions, and programmable circuitry to at least one of instantiate or execute the machine readable instructions to classify view segments associated with common homes data based on whether first return path data in respective ones of the view segments has matching panel meter data to determine labeled view segments, train a machine learning algorithm, based on a first set of features, to output media device on/off determinations to produce a machine learning algorithm, the first set of features generated from the labeled view segments, and apply second return path data to the machine learning algorithm trained to output a first on/off determination associated with a media device represented in the second return path data.

Media device on/off detection using return path data

Example methods and apparatus to onboard return path data providers for audience measurement are disclosed herein. Example apparatus disclosed herein to predict return path data quality include a classification engine to compute a first data set of model features from validation tuning data reported from media metering devices and a second data set of model features from return path data reported from return path data devices. The example apparatus also include a prediction engine to train a machine learning algorithm based on the first data set, apply the trained machine learning algorithm to the second data set to predict quality of the return path data reported from the return path data devices, and determine an onboarding status for a return path data provider based on an aggregate predicted quality of the return path data reported from the return path data devices.

Onboarding of return path data providers for audience measurement

Example methods disclosed herein include accessing common homes data for a group of common homes, the common homes data including return path data and panel meter data. Disclosed example methods also include accessing common homes data for a group of common homes, the common homes data including first return path data and corresponding panel meter data associated with respective ones of the common homes, grouping the common homes data into view segments, classifying the view segments based on whether the return path data in respective ones of the view segments has matching panel meter data to determine labeled view segments, generating features from the labeled view segments, training a machine learning algorithm based on the features, and applying second return path data to the trained machine learning algorithm to determine whether a media device associated with the second return path data is on or off.

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Chicago, IL, United States of America

Demetrios Fassois