This is the implementation of our paper "A Single Vector Is Not Enough: Taxonomy Expansion via Box Embeddings", published in WWW'23.
The original data used could be access from SemEval-2016 Task 13: Taxonomy Extraction Evaluation.
We also provide our processed data under the data
folder. Credits to repo!
All required packages could be found in requirement.txt
(generated by pip freeze
).
cd ./src
python main.py
Key Arguments Interpretation:
-
--dataset
: Dataset option: environment or science. -
--embed_size
: Dimension of box embeddings. -
--margin
: Margin for containing loss ($\delta$ in paper). -
--epsilon
: Margin for negative contain ($\epsilon$ in paper). -
--size
: Minimum box ($\phi$ in paper).
The results (log, predictions, learned boxes) are stored under the result
folder.
Song Jiang songjiang@cs.ucla.edu
@inproceedings{boxtaxo,
title={A Single Vector Is Not Enough: Taxonomy Expansion via Box Embeddings},
author={Song Jiang, Qiyue Yao, Qifan Wang, Yizhou Sun},
booktitle={Proceedings of The Web Conference},
year={2023}
}