UPD: regarding the very useful comment by Oren, I see that I did really cut it too far describing differencies of word2vec and LDA – in fact they are not so different from algorithmic point of view. So I corrected this post. Errare humanum est, stultum est in errore perseverare, you know. Also, now I really recommend you to read this presentation of Yoav Goldberg
A few days ago I found out that there had appeared lda2vec (by Chris Moody) – a hybrid algorithm combining best ideas from well-known LDA (Latent Dirichlet Allocation) topic modeling algorithm and from a bit less well-known tool for language modeling named word2vec.
You can also read this text in Russian, if you like.
And now I’m going to tell you a tale about lda2vec and my attempts to try it and compare with simple LDA implementation (I used gensim package for this). So, once upon a time…
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