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Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning

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Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning - Pilehvar, Mohammad Taher, and Camacho-Collados, Jose
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Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book ...

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Embeddings in Natural Language Processing: Theory and Advances in Vector Representations of Meaning 2020, Springer, Cham

ISBN-13: 9783031010491

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