Moving beyond the distributional model for word representation

In any modern machine learning based natural language processing (NLP) pipeline, word vectorization is a quintessential step, since we can’t feed words directly. In word vectorization, we typically assign an n-dimensional vector to a word, which captures its meaning. Consequentially, this is one of the most important steps in the pipeline since a bad representation …

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