Abstract
A low-latency reporting mechanism that runs as a layer on top of an analytics engine is described. The analytics engine runs a predictive model to generate one or more metrics related to online content usage in near future. The predictive model is based on artificial intelligence and machine learning. The predictive model can be trained with low-latency real-time event data as well as canonical data obtained from historical event logs.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Shon, Aaron; Tibell, Charles Johan Larsson; and Henriksson, Axel Erik Olov, "SYSTEMS AND METHODS FOR PREDICTING ONLINE VIDEO METRICS", Technical Disclosure Commons, (December 14, 2018)
https://www.tdcommons.org/dpubs_series/1776
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