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Complex logical query answering (CLQA) in knowledge graphs (KGs) goes beyond simple KG completion and aims at answering compositional queries comprised of multiple projections and logical operations.
Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Embedding logical queries on knowledge graphs
Will Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, and Jure Leskovec · 2018
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Graph attention networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
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Fast graph representation learning with PyTorch Geometric
Matthias Fey and Jan E. Lenssen · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Message passing query embedding
Daniel Daza and Michael Cochez · 2020
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Beta embeddings for multi-hop logical reasoning in knowledge graphs
Hongyu Ren and Jure Leskovec · 2020
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Query2box: Reasoning over knowledge graphs in vector space using box embeddings
Hongyu Ren, Weihua Hu, and Jure Leskovec · 2020
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Faithful embeddings for knowledge base queries
Haitian Sun, Andrew Arnold, Tania Bedrax Weiss, Fernando Pereira, and William W Cohen · 2020
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Inductive relation prediction by subgraph reasoning
Komal Teru, Etienne Denis, and Will Hamilton · 2020
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Composition-based multi-relational graph convolutional networks
Shikhar Vashishth, Soumya Sanyal, Vikram Nitin, and Partha Talukdar · 2020
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Complex query answering with neural link predictors
Erik Arakelyan, Daniel Daza, Pasquale Minervini, and Michael Cochez · 2021
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Neural bellman-ford networks: A general graph neural network framework for link prediction
Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal Xhonneux, and Jian Tang · 2021
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Query embedding on hyper-relational knowledge graphs
Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, and Mikhail Galkin · 2022
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Neural methods for logical reasoning over knowledge graphs
Alfonso Amayuelas, Shuai Zhang, Xi Susie Rao, and Ce Zhang · 2022
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Weisfeiler and leman go relational
Pablo Barcelo, Mikhail Galkin, Christopher Morris, and Miguel Romero Orth · 2022
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Fuzzy logic based logical query answering on knowledge graphs
Xuelu Chen, Ziniu Hu, and Yizhou Sun · 2022
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Analyzing differentiable fuzzy logic operators
Emile van Krieken, Erman Acar, and Frank van Harmelen · 2022
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Knowledge graph reasoning with relational digraph
Yongqi Zhang and Quanming Yao · 2022
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Knowledge sheaves: A sheaf-theoretic framework for knowledge graph embedding
Thomas Gebhart, Jakob Hansen, and Paul Schrater · 2023
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Relational message passing for fully inductive knowledge graph completion
Yuxia Geng, Jiaoyan Chen, Jeff Z Pan, Mingyang Chen, Song Jiang, Wen Zhang, and Huajun Chen · 2023
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A theory of link prediction via relational weisfeiler-leman on knowledge graphs
Xingyue Huang, Miguel Romero Orth, Ismail Ilkan Ceylan, and Pablo Barcelo · 2023
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InGram: Inductive knowledge graph embedding via relation graphs
Jaejun Lee, Chanyoung Chung, and Joyce Jiyoung Whang · 2023
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TFLEX: Temporal feature-logic embedding framework for complex reasoning over temporal knowledge graph
Xueyuan Lin, Haihong E, Chengjin Xu, Gengxian Zhou, Haoran Luo, Tianyi Hu, Fenglong Su, Ningyuan Li, and Mingzhi Sun · 2023
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Neural-symbolic models for logical queries on knowledge graphs
Zhaocheng Zhu, Mikhail Galkin, Zuobai Zhang, and Jian Tang · 2022
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Adapting neural link predictors for data-efficient complex query answering
Erik Arakelyan, Pasquale Minervini, Daniel Daza, and Michael Cochez Isabelle Augenstein · 2023
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Answering complex logical queries on knowledge graphs via query computation tree optimization
Yushi Bai, Xin Lv, Juanzi Li, and Lei Hou · 2023
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A neuro-symbolic framework for answering conjunctive queries
Pablo Barceló, Tamara Cucumides, Floris Geerts, Juan Reutter, and Miguel Romero · 2023
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Generalizing to unseen elements: A survey on knowledge extrapolation for knowledge graphs
Mingyang Chen, Wen Zhang, Yuxia Geng, Zezhong Xu, Jeff Z Pan, and Huajun Chen · 2023
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LitCQD: Multi-hop reasoning in incomplete knowledge graphs with numeric literals
Caglar Demir, Michel Wiebesiek, Renzhong Lu, Axel-Cyrille Ngonga Ngomo, and Stefan Heindorf · 2023
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Hongyu Ren, Mikhail Galkin, Michael Cochez, Zhaocheng Zhu, and Jure Leskovec · 2023
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Logical message passing networks with one-hop inference on atomic formulas
Zihao Wang, Yangqiu Song, Ginny Y. Wong, and Simon See · 2023
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EFO k \text{EFO}_{k} -cqa: Towards knowledge graph complex query answering beyond set operation
Hang Yin, Zihao Wang, Weizhi Fei, and Yangqiu Song · 2023
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Adaprop: Learning adaptive propagation for graph neural network based knowledge graph reasoning
Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, and Bo Han · 2023
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An ood multi-task perspective for link prediction with new relation types and nodes
Jincheng Zhou, Beatrice Bevilacqua, and Bruno Ribeiro · 2023
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A*net: A scalable path-based reasoning approach for knowledge graphs
Zhaocheng Zhu, Xinyu Yuan, Mikhail Galkin, Sophie Xhonneux, Ming Zhang, Maxime Gazeau, and Jian Tang · 2023
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Towards foundation models for knowledge graph reasoning
Mikhail Galkin, Xinyu Yuan, Hesham Mostafa, Jian Tang, and Zhaocheng Zhu · 2024
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Rethinking complex queries on knowledge graphs with neural link predictors
Hang Yin, Zihao Wang, and Yangqiu Song · 2024
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