Word-Embeddings-ukWaC

Pre-trained word embeddings using ukWaC corpus.

This repository includes links to download pre-trained word embeddings of different models using ukWaC corpus. These embeddings have been used in the following research papaers:

• Compositional Approaches for Representing Relations Between Words: A Comparative Study
• Why does PairDiff work? – A Mathematical Analysis of Bilinear Relational Compositional Operators for Analogy Detection
• Learning Relation Representations from Word Representations

Pre-trained Word Embeddings

• Continous Bag of Words (CBOW) 300 dimensions, download
• Skip-Gram (SG) 300 dimensions, download
• Global Vectors (GloVe) 300 dimensions, Download
• Latent Semantic Analysis with Singular Value Decomposition (LSA-SVD), download
• Latent Semantic Analysis with Non-negative Matrix Factorisation (LSA-NMF), download

Read Word Embeddings

To read word embeddings, use wordrep.py script in this repository.