Abstract

The large number of available content options from streaming audio and video service providers poses a challenge for providing useful recommendations to users, especially when a group of users with diverse viewing interests want to collectively engage with content. This disclosure describes techniques that leverage a large language model to generate a feature dataset based on user-permitted metadata for individual users of a group of users and content metadata for available content. A composite rating for individual pieces of content is determined and suitable content for the group is identified.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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