Company2Vec

The following repository includes the code and pre-trained cross-lingual word embeddings from the paper Learning Company Embeddings from Annual Reports for Fine-grained Industry Characterization (FinNLP 2020).

Code

In the following you can find how to easily get your relation embeddings given a corpus.

Requirements:

• Python 3.8.2

Dataset and Models

You can download the dataset and models from the followlig link

Run Code

A number of optional parameters can be specified to your needs:

*-training (English) *: English/learning.ipynb.

*-training (English) *: English/evaluation.ipynb.

*-training (Japanese) *: Japanese/learning.ipynb.

*-training (Japanese) *: Japanese/evaluation.ipynb.

Reference paper

If you use any of these resources, please cite the following paper:

@InProceedings{tomokicompany2vec,
  author = 	"Tomoki Ito, Jose Camacho Collados, Hiroki Sakaji and Steven Schockaert",
  title = 	"Learning Company Embeddings from Annual Reports for Fine-grained Industry Characterization",
  booktitle = 	"Proceedings of The  2nd Workshop on Financial Technology and Natural Language Processing",
  year = 	"2020"
}

License

Code and data in this repository are released open-source.

Copyright (C) 2020, Tomoki Ito.