Utilizing a neural network model to predict content memorability based on external and biometric factors
Abstract:
A device may receive target user category data identifying a target user, daily user data associated with the target user, real-time user data associated with the target user, and content data. The device may convert the target user category data, the daily user data, the real-time user data, and the content data into embedded target user category data, embedded daily user data, embedded real-time user data, and embedded content data. The device may process the embedded target user category data, the embedded daily user data, and the embedded real-time user data, with a neural network model, to determine a real-time user state and may determine a real-time user memory score. The device may process the embedded content data, the real-time user state, and the real-time user memory score, with the neural network model, to determine a memorability score and may perform one or more actions based on the memorability score.
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