Learning Word Vectors for Sentiment Analysis
Latent Dirichlet Allocation (LDA; (Blei et al., 2003)) is a probabilistic document model that as-sumes each document is a mixture of latent top-ics. For each latent topic T, the model learns a conditional distribution p(wjT) for the probability that word w occurs in T. One can obtain a k-dimensional vector representation of words by first
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