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Word2vec, LDA, and introducing a new hybrid algorithm: lda2vec

by juxtaposicion on 1/17/16, 3:42 PM with 11 comments

• by nl on 1/18/16, 11:32 AM

  This looks really interesting, but it pretty hard to follow without the video.

  My summary after a quick flick through is that it is a better classification(/clustering?) model for text, because it takes Word2Vec-style similarity into account, which plain LDA doesn't. That sounds like a reasonable approach to me, and nice to see someone get it working.

  I think. Comments?

  Here is the version with notes. I haven't read this through yet: http://www.slideshare.net/ChristopherMoody3/word2vec-lda-and...

  Code here, BTW: https://github.com/cemoody/lda2vec

• by warrenmar on 1/18/16, 5:03 AM

  Previous work by Chris on word2vec

  http://multithreaded.stitchfix.com/blog/2015/03/11/word-is-w...

• by ginger_beer_m on 1/18/16, 3:30 PM

  I know word2vec and LDA separately, but what does this work do? Somehow combine the word similarities from word2vec when forming LDA topics?

• by meeper16 on 1/18/16, 9:03 AM

  Word2Vec is based on an original approach from Lawrence Berkeley National Lab. This was also at the same time that David Blei was working on LDA at Berkeley. https://www.kaggle.com/c/word2vec-nlp-tutorial/forums/t/1234...

• by xuewei4d on 1/19/16, 3:10 PM

  what does v_client mean in the page 108 of the slides?

• by aerioux on 1/18/16, 10:15 AM

  awesome work :)