comScore. has been granted a patent for a method that predicts active viewability of content using historical and current viewing data. The approach involves training a machine learning model to assess whether playback devices are powered on or off, influencing subsequent actions based on these predictions. GlobalData’s report on comScore gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Predicting active viewability using historical and current viewing data
The patent US12075125B2 outlines a method and apparatus for utilizing historical viewing data to predict the operational status of a playback device, specifically whether it is powered on or off. The method involves collecting two sets of viewing data: one when the playback device is powered on and the tuner or set-top box is active, and another when the playback device is off but the tuner or set-top box remains powered. A machine learning model is trained using this data to analyze current viewing conditions and predict the playback device's status for specific timeframes. Based on this prediction, the system can determine whether to execute certain functions, such as inserting targeted advertisements or performing firmware updates and maintenance activities.
Additionally, the patent describes an apparatus that includes processors and memory, which executes instructions to carry out the aforementioned method. The historical viewing data can encompass various activities, including channel changes and program playback, while the current viewing data may reflect factors like the day, network genre, or content distribution type. The patent also covers a non-transitory computer-readable medium that stores the necessary instructions for implementing this predictive functionality, emphasizing the integration of machine learning in optimizing user engagement and device management in media consumption contexts.
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