The document recommends using an item-based recommender system that clusters similar items together and recommends other items in the same clusters to users based on their preferences, in order to provide more personalized recommendations that scale well with large amounts of data and users. It also suggests periodically updating the item similarities based on new user feedback to improve recommendations over time.

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