Abstract
The large number of channels available on television can make the process of searching for the appropriate TV channel cumbersome and time consuming. This disclosure describes techniques to make real-time personalized recommendations for live TV programming, implemented with the user’s permission. The recommendations are based on the application of a trained machine learning model. Upon being turned on, the TV is automatically tuned to a channel showing the program that is identified as being most likely to be watched by the user, chosen from all programs available at that time. Further, the user is shown a dynamically updated personalized shortlist of other channels that are broadcasting programs of likely interest to the user. Further, a notification can be shown to alert the user when a channel other than the one currently being watched starts broadcasting a program the user is likely to find of greater interest that the one on the current channel.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Calvo, Marcos and Pastor, Joan, "Dynamically updated personalized recommendations for broadcast television", Technical Disclosure Commons, (September 04, 2019)
https://www.tdcommons.org/dpubs_series/2461