Probabilistic modeling for anonymized data integration and bayesian survey measurement of sparse and weakly-labeled datasets

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United States of America Patent

PATENT NO 11568215
APP PUB NO 20210019603A1
SERIAL NO

16886379

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Abstract

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Example methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to perform probabilistic modeling for anonymized data integration and measurement of sparse and weakly-labeled datasets are disclosed. An apparatus includes a training controller to train a neural network to produce a trained neural network to output model parameters of a probability model, a model evaluator to execute the trained neural network on input data specifying a time of day, a media source, and at least one feature different from the time of day and the media source to determine one or more first model parameters of the probability model, and a ratings metric generator to evaluate the probability model based on input census data to determine a ratings metric corresponding to the time of day, the media source, and the at least one feature, the probability model configured with the one or more first model parameters.

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Patent Owner(s)

  • THE NIELSEN COMPANY (US), LLC.

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Baris, Tara Zeynep New York, US 2 7
Friedman, Joshua Ivan New York, US 8 20
Parekh, Neel New York, US 3 8

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