https://github.com/abductivelearning/abl-kg
https://github.com/abductivelearning/abl-kg
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/abductivelearning/abl-kg
- Owner: AbductiveLearning
- Created: 2023-05-12T15:03:14.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-01-31T05:58:30.000Z (over 2 years ago)
- Last Synced: 2025-04-02T02:46:29.271Z (about 1 year ago)
- Language: Python
- Size: 30.1 MB
- Stars: 8
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
🌟 **New!** [ABLkit](https://github.com/AbductiveLearning/ABLkit) released: A toolkit for Abductive Learning with high flexibility, user-friendly interface, and optimized performance. Welcome to try it out!🚀
# Enabling Abductive Learning to Exploit Knowledge Graph
This is the sample code of the experiments in [Enabling Abductive Learning to Exploit Knowledge Graph](https://www.ijcai.org/proceedings/2023/0427.pdf) in IJCAI 2023.
Four experiments are included in the paper. Please refer to each folder for each experiment:
- Animal Classification (*animal_classification*)
- Entity Alignment (*entity_alignment*)
- Link Prediction (*link_prediction*)
- Image Classification (*image_classification*)
### Reference
```
@inproceedings{ABL-KG2023Huang,
author = {Huang, Yu-Xuan and Sun, Zequn and Li, Guangyao and Tian, Xiaobin and Dai, Wang-Zhou and Hu, Wei and Jiang, Yuan and Zhou, Zhi-Hua},
title = {Enabling Abductive Learning to Exploit Knowledge Graph},
booktitle = {Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI'23)},
pages = {3839--3847},
year = {2023}
}
```