Learning from Novel Knowledge: Continual Few-shot Knowledge Graph Completion

Zhuofeng Li; Haoxiang Zhang; Qiannan Zhang; Ziyi Kou; Shichao Pei

doi:10.1145/3627673.3679734

Learning from Novel Knowledge: Continual Few-shot Knowledge Graph Completion

Zhuofeng Li
, Haoxiang Zhang
, Qiannan Zhang
, Ziyi Kou
, Shichao Pei

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	CIKM 2024 - Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
Publisher	Association for Computing Machinery
Pages	1326-1335
Number of pages	10
ISBN (Electronic)	9798400704369
DOIs	https://doi.org/10.1145/3627673.3679734
State	Published - Oct 21 2024
Event	33rd ACM International Conference on Information and Knowledge Management, CIKM 2024 - Boise, United States Duration: Oct 21 2024 → Oct 25 2024

Publication series

Name	International Conference on Information and Knowledge Management, Proceedings
ISSN (Print)	2155-0751

Conference

Conference	33rd ACM International Conference on Information and Knowledge Management, CIKM 2024
Country/Territory	United States
City	Boise
Period	10/21/24 → 10/25/24

ASJC Scopus Subject Areas

General Business,Management and Accounting
General Decision Sciences

Keywords

continual learning
few-shot learning
knowledge graphs

Access to Document

10.1145/3627673.3679734

Cite this

Li, Z., Zhang, H., Zhang, Q., Kou, Z., & Pei, S. (2024). Learning from Novel Knowledge: Continual Few-shot Knowledge Graph Completion. In CIKM 2024 - Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (pp. 1326-1335). (International Conference on Information and Knowledge Management, Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3627673.3679734

Learning from Novel Knowledge: Continual Few-shot Knowledge Graph Completion. / Li, Zhuofeng; Zhang, Haoxiang; Zhang, Qiannan et al.
CIKM 2024 - Proceedings of the 33rd ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, 2024. p. 1326-1335 (International Conference on Information and Knowledge Management, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Li, Z, Zhang, H, Zhang, Q, Kou, Z & Pei, S 2024, Learning from Novel Knowledge: Continual Few-shot Knowledge Graph Completion. in CIKM 2024 - Proceedings of the 33rd ACM International Conference on Information and Knowledge Management. International Conference on Information and Knowledge Management, Proceedings, Association for Computing Machinery, pp. 1326-1335, 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, United States, 10/21/24. https://doi.org/10.1145/3627673.3679734

Li Z, Zhang H, Zhang Q, Kou Z, Pei S. Learning from Novel Knowledge: Continual Few-shot Knowledge Graph Completion. In CIKM 2024 - Proceedings of the 33rd ACM International Conference on Information and Knowledge Management. Association for Computing Machinery. 2024. p. 1326-1335. (International Conference on Information and Knowledge Management, Proceedings). doi: 10.1145/3627673.3679734

Li, Zhuofeng ; Zhang, Haoxiang ; Zhang, Qiannan et al. / Learning from Novel Knowledge : Continual Few-shot Knowledge Graph Completion. CIKM 2024 - Proceedings of the 33rd ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, 2024. pp. 1326-1335 (International Conference on Information and Knowledge Management, Proceedings).

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title = "Learning from Novel Knowledge: Continual Few-shot Knowledge Graph Completion",

keywords = "continual learning, few-shot learning, knowledge graphs",

author = "Zhuofeng Li and Haoxiang Zhang and Qiannan Zhang and Ziyi Kou and Shichao Pei",

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AU - Pei, Shichao

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Learning from Novel Knowledge: Continual Few-shot Knowledge Graph Completion

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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