Researchers have developed "Epicure," a set of three skip-gram embeddings trained on a large multilingual recipe corpus. These embeddings are designed to capture the relationships between food ingredients, considering both co-occurrence in recipes and chemical compound data. The models, named Cooc, Chem, and Core, offer different balances between recipe context and chemical properties, providing a nuanced understanding of ingredient interactions. AI
IMPACT Introduces novel embeddings for food ingredients, potentially enabling new applications in recipe generation and food science.
RANK_REASON The cluster contains an academic paper detailing a new method for creating embeddings.
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