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Scalable Approach for Normalizing E-commerce Text Attributes (SANTA)
Experiments on a real-world attribute normalization dataset of 50 attributes show that the embeddings trained using our proposed approach obtain 2. 3% improvement over best string matching and 19. 3% improvement over best unsupervised embeddings.
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