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Amazon Personalize improves quality for batch recommendations by using the latest streamed data

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Amazon Personalize now uses the latest streamed data for batch recommendations, improving recommendation quality by capturing recent user interactions. Batch recommendations now use newly recorded events streamed via Personalize’s event tracker to generate recommendations without requiring retraining of the model. Previously, batch recommendations would only consider the interactions up to the point of the last model retraining. By considering more recent interactions, Personalize’s recommendations can now better respond to shifts in user behavior.

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