research-article

Weakly Supervised Entity Alignment with Positional Inspiration

Authors:

Hao YangAuthors Info & Claims

WSDM '23: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining

Pages 814 - 822

https://doi.org/10.1145/3539597.3570394

Published: 27 February 2023 Publication History

Abstract

The current success of entity alignment (EA) is still mainly based on large-scale labeled anchor links. However, the refined annotation of anchor links still consumes a lot of manpower and material resources. As a result, an increasing number of works based on active learning, few-shot learning, or other deep network learning techniques have been developed to address the performance bottleneck caused by a lack of labeled data. These works focus either on the strategy of choosing more informative labeled data or on the strategy of model training, while it remains opaque why existing popular EA models (e.g., GNN-based models) fail the EA task with limited labeled data. To overcome this issue, this paper analyzes the problem of weakly supervised EA from the perspective of model design and proposes a novel weakly supervised learning framework, Position Enhanced Entity Alignment (PEEA). Besides absorbing structural and relational information, PEEA aims to increase the connections between far-away entities and labeled ones by incorporating positional information into the representation learning with a Position Attention Layer (PAL). To fully utilize the limited anchor links, we further introduce a novel position encoding method that considers both anchor links and relational information from a global view. The proposed position encoding will be fed into PEEA as additional entity features. Extensive experiments on public datasets demonstrate the effectiveness of PEEA.

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Cited By

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https://doi.org/10.26599/BDMA.2024.9020082
Yoon SKo SKim TKang SYeo JLee DNejdl WAuer SKarras OCha MMoens MNajork M(2025)Unsupervised Robust Cross-Lingual Entity Alignment via Neighbor Triple Matching with Entity and Relation TextsProceedings of the Eighteenth ACM International Conference on Web Search and Data Mining10.1145/3701551.3703500(184-193)Online publication date: 10-Mar-2025
https://dl.acm.org/doi/10.1145/3701551.3703500
Zeng KJin HLv XZhu FHou LZhang YPang FQi YLiu DLi JFeng L(2024)XLORE 3: A Large-Scale Multilingual Knowledge Graph from Heterogeneous Wiki Knowledge ResourcesACM Transactions on Information Systems10.1145/366052142:6(1-47)Online publication date: 19-Aug-2024
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Index Terms

Weakly Supervised Entity Alignment with Positional Inspiration
1. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Conferences

WSDM '23: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining

February 2023

1345 pages

ISBN:9781450394079

DOI:10.1145/3539597

General Chairs:
Tat-Seng Chua
National University of Singapore
,
Hady Lauw
Singapore Management University
,
Program Chairs:
Luo Si
Salesforce
,
Evimaria Terzi
Boston University
,
Panayiotis Tsaparas
University of Ioannina

Copyright © 2023 ACM.

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Published: 27 February 2023

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National Natural Science Foundation of China
Ministry of Education and China Mobile Joint Fund
China Postdoctoral Science Foundation

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WSDM '23

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WSDM '23: The Sixteenth ACM International Conference on Web Search and Data Mining

February 27 - March 3, 2023

Singapore, Singapore

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Cited By

Cheng BZhu JDe Meo P(2025)Dual Context Representation Learning Framework for Entity AlignmentBig Data Mining and Analytics10.26599/BDMA.2024.90200828:2(346-363)Online publication date: Apr-2025
https://doi.org/10.26599/BDMA.2024.9020082
Yoon SKo SKim TKang SYeo JLee DNejdl WAuer SKarras OCha MMoens MNajork M(2025)Unsupervised Robust Cross-Lingual Entity Alignment via Neighbor Triple Matching with Entity and Relation TextsProceedings of the Eighteenth ACM International Conference on Web Search and Data Mining10.1145/3701551.3703500(184-193)Online publication date: 10-Mar-2025
https://dl.acm.org/doi/10.1145/3701551.3703500
Zeng KJin HLv XZhu FHou LZhang YPang FQi YLiu DLi JFeng L(2024)XLORE 3: A Large-Scale Multilingual Knowledge Graph from Heterogeneous Wiki Knowledge ResourcesACM Transactions on Information Systems10.1145/366052142:6(1-47)Online publication date: 19-Aug-2024
https://dl.acm.org/doi/10.1145/3660521
Tang WWang YGurrin CKongkachandra RSchoeffmann KDang-Nguyen DRossetto LSatoh SZhou L(2024)Multi-modal Entity Alignment via Position-enhanced Multi-label PropagationProceedings of the 2024 International Conference on Multimedia Retrieval10.1145/3652583.3658085(366-375)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.1145/3652583.3658085
Xu BLu YSu BYan X(2024)Position-Aware Active Learning for Multi-Modal Entity AlignmentICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP48485.2024.10447624(8215-8219)Online publication date: 14-Apr-2024
https://doi.org/10.1109/ICASSP48485.2024.10447624
Lu CXu XZhang B(2024)Modification and completion of geological structure knowledge graph based on pattern matchingScientific Reports10.1038/s41598-024-60618-114:1Online publication date: 29-Apr-2024
https://doi.org/10.1038/s41598-024-60618-1
Liang YCai WYang MJiang Y(2024)An unsupervised multi-view contrastive learning framework with attention-based reranking strategy for entity alignmentNeural Networks10.1016/j.neunet.2024.106583179(106583)Online publication date: Nov-2024
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Yan ZPeng RWu H(2024)Similarity propagation based semi-supervised entity alignmentEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.107787130:COnline publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1016/j.engappai.2023.107787
Zhang YZhu XHu X(2024)Entity alignment in noisy knowledge graphApplied Intelligence10.1007/s10489-024-06131-455:3Online publication date: 23-Dec-2024
https://doi.org/10.1007/s10489-024-06131-4
Tang WSun HWang JQi QWang JYang HTao SChen HDuh WHuang HKato MMothe JPoblete B(2023)Multi-order Matched Neighborhood Consistent Graph Alignment in a Union Vector SpaceProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3591735(963-972)Online publication date: 19-Jul-2023
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