Learning Methods for Knowledge-Enhanced Word Embeddings

Repository to contain code and information for:

Knowledge-Enhanced Word Embeddings for IR

Requirements

• ElasticSearch 6.6
• Python 3
  • Numpy
  • TensorFlow >= 1.13
  • Whoosh
  • SQLite3
  • Cvangysel
  • Pytrec_Eval
  • Scikit-Learn
  • Tqdm
  • QuickUMLS
  • Elasticsearch
  • Elasticsearch_dsl
• UMLS 2018AA

Additional Notes

server.py needs to be substitued within QuickUMLS folder as it contains a modified version required to run knowledge-enhanced models.
The folder structure required to run experiments can be seen in folder example. Python files need to be put in root.
Qrels file needs to be in .txt format.
To perform retrofitting models run retrofit_word_vecs.py, to perform the alternate learning model run tf_run_jointcrm.py, and to perform the joint learning model run tf_run_ccbow.py.
To run BM25 or QLM, use the Jupyter Notebook file elastic_search.ipynb.
To perform re-ranking run reranking.py.