Abstract
User interaction with a server that provides online services such as social networking, media hosting and sharing websites, news, etc. is detected. The user interaction and other data such as user profile information is analyzed using machine-learning models trained to detect emotion. Available content items, such as user-provided content items and sponsored content items, are matched to the detected emotion based on various criteria to select and deliver particular content items to deliver to the requesting user. The described techniques for selection and delivery of content items based on detected emotion enable delivery of content items that have a high likelihood of providing a quality user experience and improve engagement of the user with the online service.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Anonymous, "User Emotion Based Selective Delivery Of Content", Technical Disclosure Commons, (December 28, 2018)
https://www.tdcommons.org/dpubs_series/1823