Source code for the ACL 2020 paper "SEEK: Segmented Embedding of Knowledge Graphs".
make && ./main -dataset DB100K -num_thread 24 -model_path seek.model
./main -dataset DB100K -num_thread 24 -model_path seek.model -prediction 1
./main -dataset DB100K -num_thread 24 -model_path seek.model -classification 1
| Option | Description |
|---|---|
| -dataset | Dataset |
| -num_thread | Number of threads |
| -embed_dim | Dimension of embeddings |
| -num_seg | Number of segments |
| -neg_sample | Negatives samples |
| -num_epoch | Epochs for training |
| -model_path | Model path |
| -lambda | L2 weight regularization penalty |
| -lr | Init learning rate |
Please cite the following paper if you use this code in your work.
@inproceedings{xu-etal-2020-seek,
title = "{SEEK}: Segmented Embedding of Knowledge Graphs",
author = "Xu, Wentao and Zheng, Shun and He, Liang and Shao, Bin and Yin, Jian and Liu, Tie-Yan",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.acl-main.358",
pages = "3888--3897",
}
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