METHODS AND APPARATUS TO MODEL SET-TOP BOX DATA
First Claim
1. A method of calculating a behavior probability comprising:
- receiving a first set of non-panelist behavior data;
receiving a second set of panelist set-top box behavior data, the second set being associated with demographic data;
identifying at least one behavior pattern common to the first and second sets of behavior data; and
fusing data associated with the at least one behavior pattern from the first set with data associated with the at least one behavior pattern from the second set to impute at least one demographic characteristic from the second set to the first set and generate a quantity of household tuning minutes.
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Accused Products
Abstract
Methods and apparatus to model set-top box data are disclosed. An example method includes receiving a first set of non-panelist behavior data and receiving a second set of panelist set-top box behavior data, the second set being associated with demographic data. The example method also includes identifying at least one behavior pattern common to the first and second sets of behavior data, and fusing data associated with the at least one behavior pattern from the first set with data associated with the at least one behavior pattern from the second set to impute at least one demographic characteristic from the second set to the first set and generate a quantity of household tuning minutes.
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Citations
31 Claims
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1. A method of calculating a behavior probability comprising:
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receiving a first set of non-panelist behavior data; receiving a second set of panelist set-top box behavior data, the second set being associated with demographic data; identifying at least one behavior pattern common to the first and second sets of behavior data; and fusing data associated with the at least one behavior pattern from the first set with data associated with the at least one behavior pattern from the second set to impute at least one demographic characteristic from the second set to the first set and generate a quantity of household tuning minutes. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. An apparatus to calculate a viewing probability comprising:
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a deletion factor engine to apply at least one deletion factor to received non-panelist set-top box data; a characteristics imputation engine to fuse the received non-panelist set-top box data with at least one demographic characteristic to generate fused set-top box data; and a viewing probability engine to calculate the viewing probability for at least one audience member based on the fused set-top box data and demographics data. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25, 26, 27)
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28. An article of manufacture storing machine readable instructions which, when executed, cause a machine to:
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receive a first set of non-panelist behavior data; receive a second set of panelist set-top box behavior data, the second set being associated with demographic data; identify at least one behavior pattern common to the first and second sets of behavior data; and fuse data associated with the at least one behavior pattern from the first set with data associated with the at least one behavior pattern from the second set to impute at least one demographic characteristic from the second set to the first set and generate a quantity of household tuning minutes. - View Dependent Claims (29, 30)
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31-39. -39. (canceled)
Specification