Which mathematical approach has shown the highest accuracy rate in retail recommendation systems according to recent industry benchmarks?

Mathematics has revolutionized how retail products are marketed and sold. Behind every successful retail recommendation system lies sophisticated algorithms and statistical models that predict consumer preferences with remarkable accuracy. This poll tests your knowledge about how mathematical concepts are applied in modern retail recommendation systems to enhance the customer experience and drive sales. Can you identify which approach has mathematically proven to be most effective?

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Collaborative filtering using singular value decomposition (SVD)
Content-based filtering using cosine similarity metrics
Association rule learning with Apriori algorithm
Deep learning models with recurrent neural networks (RNN)