Conditional Logical Message Passing Transformer for Complex Query Answering-Reference-Cited by-同舟云学术

Conditional Logical Message Passing Transformer for Complex Query Answering

Published:2024-08-24 Issue: Volume:34 Page:4119-4130
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Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Zhang Chongzhi¹^ORCID,Peng Zhiping²^ORCID,Zheng Junhao¹^ORCID,Ma Qianli¹^ORCID

Affiliation:

1. South China University of Technology, Guangzhou, China

2. Guangdong University of Petrochemical Technology & Jiangmen Polytechnic, Maoming, China

Funder

Science and Technology Planning Project of Guangdong Province

Natural Science Foundation of Guangdong Province

National Natural Science Foundation of China

National Key R&D Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671869

Reference74 articles.

1. Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, and Mikhail Galkin. 2022. Query Embedding on Hyper-Relational Knowledge Graphs. In International Conference on Learning Representations. https://openreview.net/forum?id=4rLw09TgRw9

2. Alfonso Amayuelas, Shuai Zhang, Susie Xi Rao, and Ce Zhang. 2022. Neural Methods for Logical Reasoning over Knowledge Graphs.. In Proceedings of the Tenth International Conference on Learning Representations 2022.

3. Erik Arakelyan, Daniel Daza, Pasquale Minervini, and Michael Cochez. 2020. Complex Query Answering with Neural Link Predictors. In International Conference on Learning Representations.

4. Erik Arakelyan, Pasquale Minervini, Daniel Daza, Michael Cochez, and Isabelle Augenstein. 2023. Adapting Neural Link Predictors for Data-Efficient Complex Query Answering. In Thirty-seventh Conference on Neural Information Processing Systems.

5. Knowledge Graph Reasoning over Entities and Numerical Values