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a helper for word embeddings (word2vec, glove)
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just semantics : a helper for word embedding vectors

Disclaimer: This project is really really very early and you should only use it if you are as desperate as I was when looking for something similar

What it does

It reads the vector files produced by either word2vec or GloVe and then clusters them using weka's kmeans.


For now weka is a dependency. It is not included/packaged, but it should be easy to find.

Let's be honest, this is not a one-click situation. In any case I am providing the source code, and I trust you will know what to do. I've used weka 3.7.5 and apache-commons cli 1.2 when writing this. You should probably do the same.


There is some well-intendend help options included in the source. They might help.


For word2vec you will just need the binary vector file and a number of clusters (k for kMeans)

For GloVe you will need the binary vector file, the vocab file in txt format and the number of clusters (k for kMeans)

It currently writes no output files, but will print out the clusters.


In the extremely improbable but very welcome chance...

  1. Fork it!
  2. Create your feature branch: git checkout -b my-new-feature
  3. Commit your changes: git commit -am 'Add some feature'
  4. Push to the branch: git push origin my-new-feature
  5. Submit a pull request :D


I wrote this because I was frustrated with how difficult it was to find documentation about using the vector (binary) files. It might just be me who felt that way, but maybe it will help someone.


This was created in the context of my (Dialekti VALSAMOU) PhD work. I am affiliated to two laboratories:

  • MIG - INRA


Apache 2.0

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