Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion

Zhenwei Tang; Shichao Pei; Zhao Zhang; Yongchun Zhu; Fuzhen Zhuang; Robert Hoehndorf; Xiangliang Zhang

doi:10.24963/ijcai.2022/312

Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion

Zhenwei Tang
, Shichao Pei
, Zhao Zhang
, Yongchun Zhu
, Fuzhen Zhuang
, Robert Hoehndorf
, Xiangliang Zhang

Computer Science

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

Original language	English
Title of host publication	Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022
Editors	Luc De Raedt, Luc De Raedt
Publisher	International Joint Conferences on Artificial Intelligence
Pages	2248-2254
Number of pages	7
ISBN (Electronic)	9781956792003
DOIs	https://doi.org/10.24963/ijcai.2022/312
State	Published - 2022
Event	31st International Joint Conference on Artificial Intelligence, IJCAI 2022 - Vienna, Austria Duration: Jul 23 2022 → Jul 29 2022

Publication series

Name	IJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)	1045-0823

Conference

Conference	31st International Joint Conference on Artificial Intelligence, IJCAI 2022
Country/Territory	Austria
City	Vienna
Period	7/23/22 → 7/29/22

ASJC Scopus Subject Areas

Artificial Intelligence

Access to Document

10.24963/ijcai.2022/312

Cite this

Tang, Z., Pei, S., Zhang, Z., Zhu, Y., Zhuang, F., Hoehndorf, R., & Zhang, X. (2022). Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion. In L. De Raedt, & L. De Raedt (Eds.), Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022 (pp. 2248-2254). (IJCAI International Joint Conference on Artificial Intelligence). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2022/312

Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion. / Tang, Zhenwei; Pei, Shichao; Zhang, Zhao et al.
Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022. ed. / Luc De Raedt; Luc De Raedt. International Joint Conferences on Artificial Intelligence, 2022. p. 2248-2254 (IJCAI International Joint Conference on Artificial Intelligence).

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

Tang, Z, Pei, S, Zhang, Z, Zhu, Y, Zhuang, F, Hoehndorf, R & Zhang, X 2022, Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion. in L De Raedt & L De Raedt (eds), Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022. IJCAI International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, pp. 2248-2254, 31st International Joint Conference on Artificial Intelligence, IJCAI 2022, Vienna, Austria, 7/23/22. https://doi.org/10.24963/ijcai.2022/312

Tang Z, Pei S, Zhang Z, Zhu Y, Zhuang F, Hoehndorf R et al. Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion. In De Raedt L, De Raedt L, editors, Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022. International Joint Conferences on Artificial Intelligence. 2022. p. 2248-2254. (IJCAI International Joint Conference on Artificial Intelligence). doi: 10.24963/ijcai.2022/312

Tang, Zhenwei ; Pei, Shichao ; Zhang, Zhao et al. / Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion. Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022. editor / Luc De Raedt ; Luc De Raedt. International Joint Conferences on Artificial Intelligence, 2022. pp. 2248-2254 (IJCAI International Joint Conference on Artificial Intelligence).

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Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion

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ASJC Scopus Subject Areas

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