PVN-Post-Processing-of-word-representation-via-variance-normalization

PVN code for paper: Post-Processing of Word Representations via Variance Normalization and Dynamic Embedding

Procedure

1. Provide the word representation file as txt format. For example: https://nlp.stanford.edu/projects/glove/ You can just choose the following one. https://nlp.stanford.edu/data/glove.6B.zip

2. Edit the path from PNV.sh

   BASELINE_PATH=./sgns.words

   RESULT_PATH=./sgns.word.processed

If you are going to use vector other than 300 dimensions. Please change it from pvn.py. 3. Run PNV.sh file.

I also put the evaluation for word similarity in the same folder. You can have a easy test.

Here is some results: (same with our paper)

sgns file from our paper: Figure1.png

Results for GloVe(downloaded from office website, glove.6B.zip): Figure2.png

For details about PNV - Post-Processing via Variance Normalization, please look into the paper:

https://arxiv.org/abs/1808.06305

If you are going to use this method, please cite our paper.

@article{wang2018post,
 title={Post-Processing of Word Representations via Variance Normalization and Dynamic Embedding},
 author={Wang, Bin and Chen, Fenxiao and Wang, Angela and Kuo, C-C Jay},
 journal={arXiv preprint arXiv:1808.06305},
 year={2018}}