Which NLP innovation revolutionized retail recommendation systems in 2018-2019 by enabling them to better understand contextual word relationships?

Modern retail recommendation systems have evolved dramatically, particularly in how they process and understand language. Natural Language Processing (NLP) has transformed how retailers interpret customer preferences, reviews, and search queries. Today's advanced recommendation engines don't just match keywords—they understand context, sentiment, and even dialect variations. Test your knowledge about how linguistic technology is reshaping the retail recommendation landscape!

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• BERT (Bidirectional Encoder Representations from Transformers)
• Word2Vec
• GloVe (Global Vectors for Word Representation)
• Latent Semantic Analysis (LSA)

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