A Good Neighbor, A Found Treasure: Mining Treasured Neighbors for Knowledge Graph Entity Typing

Zhuoran Jin, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao

Abstract
The task of knowledge graph entity typing (KGET) aims to infer the missing types for entities in knowledge graphs. Some pioneering work has proved that neighbor information is very important for the task. However, existing methods only leverage the one-hop neighbor information of the central entity, ignoring the multi-hop neighbor information that can provide valuable clues for inference. Besides, we also observe that there are co-occurrence relations between types, which is very helpful to alleviate false-negative problem. In this paper, we propose a novel method called Mining Treasured Neighbors (MiNer) to make use of these two characteristics. Firstly, we devise a Neighbor Information Aggregation module to aggregate the neighbor information. Then, we propose an Entity Type Inference module to mitigate the adverse impact of the irrelevant neighbor information. Finally, a Type Co-occurrence Regularization module is designed to prevent the model from overfitting the false negative examples caused by missing types. Experimental results on two widely used datasets indicate that our approach significantly outperforms previous state-of-the-art methods.
Anthology ID:
2022.emnlp-main.31
Volume:
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Editors:
Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
480–490
Language:
URL:
https://aclanthology.org/2022.emnlp-main.31
DOI:
10.18653/v1/2022.emnlp-main.31
Bibkey:
Cite (ACL):
Zhuoran Jin, Pengfei Cao, Yubo Chen, Kang Liu, and Jun Zhao. 2022. A Good Neighbor, A Found Treasure: Mining Treasured Neighbors for Knowledge Graph Entity Typing. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 480–490, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
A Good Neighbor, A Found Treasure: Mining Treasured Neighbors for Knowledge Graph Entity Typing (Jin et al., EMNLP 2022)
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