Abstract: A system includes hardware processors and a non-transitory memory storing instructions that, when executed by the hardware processors, causes the hardware processors to perform actions including receiving an input data set related to digital content, where the input data set includes a plurality of input entries. The actions also include matching one or more input words of each input entry of the plurality of input entries to one or more baseline words of one or more baseline entries of a baseline data set and generating an output data set including a plurality of output entries. Each respective input entry corresponds to a respective output entry of the plurality of output entries, and each respective output entry includes a baseline entry of the one or more baseline entries having a highest probability of matching the respective input entry and additional data associated with the respective input entry.

Abstract: A system includes hardware processors and a non-transitory memory storing instructions that, when executed by the hardware processors, causes the hardware processors to perform actions including receiving an input data set related to digital content, where the input data set includes a plurality of input entries. The actions also include matching one or more input words of each input entry of the plurality of input entries to one or more baseline words of one or more baseline entries of a baseline data set and generating an output data set including a plurality of output entries. Each respective input entry corresponds to a respective output entry of the plurality of output entries, and each respective output entry includes a baseline entry of the one or more baseline entries having a highest probability of matching the respective input entry and additional data associated with the respective input entry.

Abstract: Systems and methods for generating telecast forecasts is provided. An automated forecasting system uses machine learning-driven a forecast model for generating forecast for various telecasts varying periods of time. Estimate values that are used to generate the forecasts may be determined based on deriving trends and correlations from telecasts data using machine learning. The forecasting system may compare estimate values and actual values associated with the various telecasts and subsequently update the forecast model based on the comparison. The forecast model may be displayed on an electronic device of a client electronic device and may be updated or influenced by telecast providers.