Abstract: Methods and apparatus to adjust media impressions based on media impression notification loss rates in network communications are disclosed.

Abstract: Methods and apparatus to partition data are disclosed. An example apparatus to partition panelist data includes an indicator matrix generator to determine an indicator matrix including panelist vectors for panelists based on panelist data associated with the panelists, a first one of the panelist vectors for a first one of the panelists to indicate whether the first one of the panelists: has a first characteristic, meets a first criterion based on the first characteristic and a second characteristic, has a third characteristic, and meets a second criterion based on the third characteristic and a fourth characteristic. The example apparatus further includes a matrix reducer to reduce the indicator matrix to a set of unique panelist vectors that represent partitions of the panelist data, the partitions of the panelist data to utilize less storage capacity than the panelist data.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to estimate demographics of users employing social media. An example method disclosed herein includes (1) identifying a social media message regarding an asset, the social media message associated with a user identifier associated with the user, (2) determining demographics associated with a group of people exposed to the asset, (3) associating the user identifier with the asset, and (4) repeating (1) to (3). The example method also includes (5) combining demographics associated with two or more different groups of people with which the user identifier is associated to estimate a demographic profile for the user.

Abstract: Methods and apparatus to determine engagement levels of audience members are disclosed. An example apparatus includes means for detecting whether an environment associated with a first device includes a second device with a display that is illuminated. The example apparatus also includes means for calculating an engagement of a user with respect to the first device based on a proximity between the user and the illuminated display.

Abstract: Methods and apparatus to determine engagement levels of audience members are disclosed. An example apparatus includes means for detecting whether an environment associated with a first device includes a second device with a display that is illuminated. The example apparatus also includes means for calculating an engagement of a user with respect to the first device based on a proximity between the user and the illuminated display.

Abstract: Methods and apparatus to determine engagement levels of audience members are disclosed. An example apparatus includes means for detecting whether an environment associated with a first device includes a second device with a display that is illuminated. The example apparatus also includes means for calculating an engagement of a user with respect to the first device based on a proximity between the user and the illuminated display.

Abstract: Methods and apparatus to determine engagement levels of audience members are disclosed. An example apparatus includes means for detecting whether an environment associated with a first device includes a second device with a display that is illuminated. The example apparatus also includes means for calculating an engagement of a user with respect to the first device based on a proximity between the user and the illuminated display.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to determine a duration of media presentation based on tuning session duration. Example apparatus a receiver to obtain a first tuning session duration indicative of an amount of time between channel changes of a first media presentation device at a first media presentation location, a presentation session estimator to select a model from storage, the model selected based on a match of the first tuning session duration and a second tuning session duration, the model including a relation between the second tuning session duration and a first presentation session duration of media presented on a second media presentation device at a second media presentation location, and estimate a second presentation session duration of media presented within the first tuning session duration based on the model.

Abstract: Methods and apparatus to correct for deterioration of a demographic model to associate demographic information with media impression information are disclosed. An example method includes estimating first and second ages of audience members based on demographic information; estimating a third age of an audience member who is not included in the audience members; applying a window function to the second ages to determine a distribution of ages based on the third age; multiplying window values by the first ages to determine corrected first age components; dividing a total of the corrected first age components by a sum of the window values to determine an estimated age of the audience member at a first time; and determining the corrected age of the audience member at a second time based on the estimated age of the audience member at the first time and a time difference between the first and second times.

Abstract: Methods and apparatus to correct for deterioration of a demographic model to associate demographic information with media impression information are disclosed. An example method includes estimating first and second ages of audience members based on demographic information; estimating a third age of an audience member who is not included in the audience members; applying a window function to the second ages to determine a distribution of ages based on the third age; multiplying window values by the first ages to determine corrected first age components; dividing a total of the corrected first age components by a sum of the window values to determine an estimated age of the audience member at a first time; and determining the corrected age of the audience member at a second time based on the estimated age of the audience member at the first time and a time difference between the first and second times.

Abstract: Methods and apparatus to estimate demographics of a household are disclosed. An example method to determine demographics for non-panelist households includes calculating a first demographic constraint average and a second demographic constraint average based on a first demographic distribution of a first tuning event of a household and a second demographic distribution of a second tuning event of the household. The household is a non-panelist household. The example method also includes, based on the first demographic constraint average, determining a first likelihood of the household being associated with a first demographic constraint. The example method also includes, based on the second demographic constraint average, determining a second likelihood of the household being associated with a second demographic constraint. The example method also includes estimating a household characteristic of the household based on the first likelihood and the second likelihood.

Abstract: Methods and apparatus to adjust media impressions based on media impression notification loss rates in network communications are disclosed.

Abstract: Methods and apparatus to determine engagement levels of audience members are disclosed. An example apparatus includes means for detecting whether an environment associated with a first device includes a second device with a display that is illuminated. The example apparatus also includes means for calculating an engagement of a user with respect to the first device based on a proximity between the user and the illuminated display.

Abstract: Methods and apparatus to generate data for geographic areas are disclosed. An example method includes identifying a first geographic area for which a database does not include a model, determining a first data element of the first geographic area, identifying a first trained model corresponding to a second geographic area with the first data element, identifying a second trained model corresponding to a third geographic area with the first data element, mixing the first trained model and the second trained model to generate a composite model, and using the composite model to represent the first geographic area in the database.

Abstract: Methods and apparatus to estimate market opportunities for an object class are disclosed. An example method includes obtaining first measurements of a set of characteristics for a first area, the set of characteristics being associated with an item class; determining a first relationship between a first probability of a population in the first area to purchase the item class and the first measurements of the set of characteristics; obtaining second measurements of the set of characteristics for a second area; and estimating a second probability of a population of the second area purchasing the item class based on applying the first relationship to the second measurements.

Abstract: Methods and apparatus to adjust media impressions based on media impression notification loss rates in network communications are disclosed.

Abstract: Methods and apparatus to determine engagement levels of audience members are disclosed. An example computer readable storage medium includes computer readable instructions that, when executed, cause a processor to at least analyze image data from a sensor to determine whether an environment in which media is to be presented by a first device includes a second device with an illuminated display, and when the environment includes the second device with the illuminated display, determine whether the illuminated display of the second device is associated with a media presentation by the second device.

Abstract: Methods and apparatus to facilitate dynamic classification for market research are disclosed. Example disclosed methods include constructing, using a programmed processor based on data for a sample population and a first set of input variables, a self-organizing map classifying the sample population according to a plurality of classes defined in the map using fuzzy class membership. Example disclosed methods include extracting the fuzzy class membership for the sample population from the map. Example disclosed methods include correlating fuzzy class membership with behavior data for the sample population to determine a likely class behavior for the plurality of classes. Example disclosed methods include using fuzzy class membership and the likely class behavior to provide a predictive market output in response to a query.

Abstract: Methods and apparatus to apply household-level weights to audience measurement data at a household-member level are disclosed. An example method to determine demographics of populations to measure media audiences of populations includes determining demographics for members of a first household of a sub-population. First demographics of a first member of the first household are different than second demographics of a second member of the first household. The example method includes calculating a first household-level weight for the first household based on a demographics distribution of the sub-population and aggregate demographics of a population.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to monitor media presentation to determine a period of media presentation based on tuning session period are disclosed. Example methods disclosed herein include determining a first tuning session based on a period of time between channel changes of a first media presentation device, determining first presentation session data within the determined first tuning session, determining a model relating the first tuning session with the first presentation session data, determine a second tuning session for tuning data from a second media presentation device, selecting the model for the second tuning session, based on a match of a first duration of the second tuning session and a second duration associated with the model, and estimating second presentation session data for the second tuning session based on the model.