Article

Bootstrapping entity alignment with knowledge graph embedding

Authors:

Qingheng Zhang,

Yuzhong QuAuthors Info & Claims

IJCAI'18: Proceedings of the 27th International Joint Conference on Artificial Intelligence

Pages 4396 - 4402

Published: 13 July 2018 Publication History

Abstract

Embedding-based entity alignment represents different knowledge graphs (KGs) as low-dimensional embeddings and finds entity alignment by measuring the similarities between entity embeddings. Existing approaches have achieved promising results, however, they are still challenged by the lack of enough prior alignment as labeled training data. In this paper, we propose a bootstrapping approach to embedding-based entity alignment. It iteratively labels likely entity alignment as training data for learning alignment-oriented KG embeddings. Furthermore, it employs an alignment editing method to reduce error accumulation during iterations. Our experiments on real-world datasets showed that the proposed approach significantly outperformed the state-of-the-art embedding-based ones for entity alignment. The proposed alignment-oriented KG embedding, bootstrapping process and alignment editing method all contributed to the performance improvement.

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Cited By

Zhang YWu JYu KWu X(2024)Diverse Structure-Aware Relation Representation in Cross-Lingual Entity AlignmentACM Transactions on Knowledge Discovery from Data10.1145/363877818:4(1-23)Online publication date: 13-Feb-2024
https://dl.acm.org/doi/10.1145/3638778
Cai LMao XXiao YWu CLan MElkind E(2023)An effective and efficient time-aware entity alignment framework via Two-aspect three-view label propagationProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/558(5021-5029)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.24963/ijcai.2023/558
Huang YSun ZLi GTian XDai WHu WJiang YZhou ZElkind E(2023)Enabling abductive learning to exploit knowledge graphProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/427(3839-3847)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.24963/ijcai.2023/427
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cover image Guide Proceedings

IJCAI'18: Proceedings of the 27th International Joint Conference on Artificial Intelligence

July 2018

5885 pages

ISBN:9780999241127

Editor:
Jérôme Lang

Sponsors

Adobe
IBMR: IBM Research
ERICSSON
Microsoft: Microsoft
AI Journal: AI Journal

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AAAI Press

Publication History

Published: 13 July 2018

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Cited By

Zhang YWu JYu KWu X(2024)Diverse Structure-Aware Relation Representation in Cross-Lingual Entity AlignmentACM Transactions on Knowledge Discovery from Data10.1145/363877818:4(1-23)Online publication date: 13-Feb-2024
https://dl.acm.org/doi/10.1145/3638778
Cai LMao XXiao YWu CLan MElkind E(2023)An effective and efficient time-aware entity alignment framework via Two-aspect three-view label propagationProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/558(5021-5029)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.24963/ijcai.2023/558
Huang YSun ZLi GTian XDai WHu WJiang YZhou ZElkind E(2023)Enabling abductive learning to exploit knowledge graphProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/427(3839-3847)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.24963/ijcai.2023/427
Chang XLiu YHuang LLi JLiang YLi SSun Y(2023)Blockchain Threat Intelligence Knowledge Graph Alignment via Graph Convolutional NetworksProceedings of the 2023 International Conference on Information Education and Artificial Intelligence10.1145/3660043.3660119(421-430)Online publication date: 22-Dec-2023
https://dl.acm.org/doi/10.1145/3660043.3660119
Ge CLiu XChen LGao YZheng B(2022)LargeEAProceedings of the VLDB Endowment10.14778/3489496.348950415:2(237-245)Online publication date: 4-Feb-2022
https://dl.acm.org/doi/10.14778/3489496.3489504
Li JSong D(2022)Uncertainty-aware Pseudo Label Refinery for Entity AlignmentProceedings of the ACM Web Conference 202210.1145/3485447.3511926(829-837)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3485447.3511926
Xie ZZhu RZhao KLiu JZhou GHuang J(2021)Dual Gated Graph Attention Networks with Dynamic Iterative Training for Cross-Lingual Entity AlignmentACM Transactions on Information Systems10.1145/347116540:3(1-30)Online publication date: 17-Nov-2021
https://dl.acm.org/doi/10.1145/3471165
Yang JWang DZhou WQian WWang XHan JHu SDemartini GZuccon GCulpepper JHuang ZTong H(2021)Entity and Relation Matching Consensus for Entity AlignmentProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482338(2331-2341)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482338
Amsterdamer YCohen MDemartini GZuccon GCulpepper JHuang ZTong H(2021)Automated Selection of Multiple Datasets for Extension by IntegrationProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482322(27-36)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482322
Peng HLi HSong YZheng VLi JDemartini GZuccon GCulpepper JHuang ZTong H(2021)Differentially Private Federated Knowledge Graphs EmbeddingProceedings of the 30th ACM International Conference on Information & Knowledge Management10.1145/3459637.3482252(1416-1425)Online publication date: 26-Oct-2021
https://dl.acm.org/doi/10.1145/3459637.3482252
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