In our recent work, Analysis of Italian Word Embeddings (arXiv preprint arXiv:1707.08783), I and Stefano analysed the effect of different hyper-perparameters on the performances of two word embeddings algorithms, skip-gram (SG) and continuous-bag-of-words (CBOW), on semantic and morphs-syntactic tasks.

 

 

The pre-trained vectors with the highest accuracy can be downloaded from the following link:

• SG-500_w-5_m-5_n10_binary

Please cite: Rocco Tripodi, Stefano Li Pira, Analysis of Italian Word Embeddings, arXiv preprint arXiv:1707.08783, if you use our them in your application.

@article{tripodi2017analysis,
title={Analysis of Italian Word Embeddings},
author={Tripodi, Rocco and Li Pira, Stefano},
journal={arXiv preprint arXiv:1707.08783},
year={2017}
}