Which NLP technique revolutionized retail recommendation systems by allowing algorithms to understand the contextual meaning of words rather than treating them as independent units?

Natural Language Processing (NLP) has transformed how retail recommendation systems understand customer preferences. Language models analyze reviews, search queries, and social media to personalize shopping experiences. As linguistics and retail technology converge, businesses are leveraging semantic analysis to better understand customer intent and deliver more relevant product suggestions. Test your knowledge of how language technology is reshaping retail recommendations!

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Word embeddings (like Word2Vec and GloVe)
Regular expression pattern matching
Syllable-based tokenization
Phonetic analysis algorithms