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A comparison of correspondence analysis with PMI-based word embedding methods
Popular word embedding methods such as GloVe and Word2Vec are related to the factorization of the pointwise mutual information (PMI) matrix.
Improving information retrieval through correspondence analysis instead of latent semantic analysis
The elements of the raw document-term matrix are weighted, and the weighting exponent of singular values is adjusted to improve the performance of LSA.
A comparison of latent semantic analysis and correspondence analysis of document-term matrices
In this article, we present a theoretical analysis and comparison of the two techniques in the context of document-term matrices.
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