Directional Skip-Gram: Explicitly Distinguishing Left and Right Context for Word Embeddings

To build the code, simply run:

make

The command to build word embeddings is exactly the same as in the original version, except that we removed the argument -cbow and replaced it with the argument -type:

./dsg -train input_file -output embedding_file -type 0 -size 50 -window 5 -negative 10 -hs 0 -sample 1e-4 -threads 1 -binary 1 -iter 5

The -type argument is a integer that defines the architecture to use. These are the possible parameters:
0 - dsg: the model proposed in this paper; 1 - simple ssg: the comparative model adopted from the original structured SG model (https://github.com/wlin12/wang2vec).

If you use functionalities in this code, please support us by citing our paper:

@InProceedings{Song:2018:naacl, author = {Yan Song and Shuming Shi and Jing Li and Haisong Zhang}, title = "{Directional Skip-Gram: Explicitly Distinguishing Left and Right Context for Word Embeddings}", booktitle = {Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies}, year = {2018}, publisher = {Association for Computational Linguistics}, address = {New Orleans, Louisiana, USA} }

Many thanks!