| CPC H04N 21/23424 (2013.01) [H04N 21/2385 (2013.01); H04N 21/4662 (2013.01)] | 20 Claims |
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1. A method, comprising:
receiving a prediction input characterizing utilization of a plurality of content stream utilization channels (CSUCs);
predicting automatically one or more schedule parameters based on the prediction input via one or more of multiple different prediction models obtained via machine learning based on training data that is generated based on historic data related to content delivery via the plurality of CSUCs, wherein the one or more schedule parameters comprise a CSUC occupancy prediction associated with a time frame in a geographical region and/or in an adapter, wherein the historic data is grouped in accordance with some criterion determined based on operational modes in which the multiple different prediction models are to operate, and wherein the multiple different prediction models are trained based on different groups of historic data, respectively;
identifying, based on the one or more schedule parameters, at least one insertion opportunity with respect to at least one CSUC;
generating, for each of the at least one insertion opportunity, a corresponding insertion schedule specifying insertion of a content stream into a selected CSUC at an insertion time; and
updating the training data based on content insertion schedules generated according to predictions made based on the one or more of multiple different prediction models, wherein the one or more of multiple different prediction models are updated based on the updated training data.
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