Book embeddings, sometimes referred to in the context of natural language processing (NLP) and machine learning, typically involve representing entire books or long-form texts as dense vectors in a high-dimensional space. This process allows complex and nuanced texts to be mathematically manipulated, making it easier to analyze, compare, and retrieve information.
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