Abstract

A context-aware content recommendation process for an application running on a computing device (e.g., a smart television, a mobile computing device) may provide context-aware content recommendations to a user on the go (e.g., during travel). The context-aware recommendation process may determine that a user on the go may have different content consumption patterns and computing device access. In some implementations, the computing device may be shared with other users (e.g., a smart television in a hotel room, a tablet belonging to a friend). The context-aware content recommendation process may interface with device sensors included on the computing device that may provide the context for user consumption. The context-aware content recommendation process may utilize, for example, Global Positioning System (GPS) data provided by the device sensors along with the use of machine learning models to determine travel states of the user. Based on a determined travel state of the user, the context-aware recommendation process may implement one or more modes of operation or states for the application running on the computing device. The context-aware content recommendation process may implement a minimalist ambient mode of operation of the application, The context-aware content recommendation process may provide wallpapers tailored to a determined context of the user. The context-aware content recommendation process may offer tailored media content recommendations for consumption by the user based on the current context of the user (e.g., short-form videos, relevant podcasts, etc.). The ability to provide context-aware content recommendations to a user on the go may provide a more relevant and convenient user experience for accessing media content while a user is in transit or is using a shared computing device.

Creative Commons License

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

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