Code used in the paper Feature2Vec: Distributional semantic modelling of human property knowledge.
Code ran on ubuntu 16.04 with anaconda python distribution with python 3.6.9. Packages include,
- numpy
- pandas
- scikit-learn
- spacy
- tensorflow-gpu
- keras-gpu
- jupyter lab
- conda_nb
python -m spacy download en_core_web_lg
Pretrained embeddings for features, along with save/load functions, are now available. The embeddings are placed in the embeddings folder as .txt files. The embeddings were trained using all concepts and features. Feature2Vec still requires the spacy word embeddings and property norm datasets to run. See tsne below for example of possible analysis.
