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The article focuses on evaluating Next Basket Recommendation (NBR) methods for suggesting items in users future shopping baskets. It discusses the distinction between repeat and explore items in recommendations, introduces novel metrics for NBR evaluation, and highlights the variations in method performance across different datasets and scenarios, shedding light on the challenges and opportunities in this area of research.