Distributed skipgram mixture model for multisense word embedding
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Distributed Multisense Word Embedding

The Distributed Multisense Word Embedding(DMWE) tool is a parallelization of the Skip-Gram Mixture [1] algorithm on top of the DMTK parameter server. It provides an efficient "scaling to industry size" solution for multi sense word embedding.

For more details, please view our website http://www.dmtk.io


$ git clone https://github.com/Microsoft/distributed_skipgram_mixture



DMWE is built on top of the DMTK parameter sever, therefore please download and build DMTK first (https://github.com/Microsoft/multiverso).

For Windows

Open windows\distributed_skipgram_mixture\distributed_skipgram_mixture.sln using Visual Studio 2013. Add the necessary include path (for example, the path for DMTK multiverso) and lib path. Then build the solution.

For Ubuntu (Tested on Ubuntu 12.04)

Download and build by running $ sh build.sh. Modify the include and lib path in Makefile. Then run $ make all -j4.


For parameter settings, see scripts/parameters_settings.txt. For running it, see the example script scripts/run.py.


[1] Tian, F., Dai, H., Bian, J., Gao, B., Zhang, R., Chen, E., & Liu, T. Y. (2014). A probabilistic model for learning multi-prototype word embeddings. In Proceedings of COLING (pp. 151-160).

Microsoft Open Source Code of Conduct

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.