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The study of machine learning-based logical query answering enables reasoning with large-scale and incomplete knowledge graphs.
On closed world data bases
Raymond Reiter. 1981 · 1981
Earlier work this paper cites.
A sound and sometimes complete query evaluation algorithm for relational databases with null values
Raymond Reiter. 1986 · 1986
Earlier work this paper cites.
The theory of probabilistic databases
Roger Cavallo and Michael Pittarelli. 1987 · 1987
Earlier work this paper cites.
Possibilistic constraint satisfaction problems or “how to handle soft constraints?”
Thomas Schiex. 1992 · 1992
Earlier work this paper cites.
WordNet: A lexical database for English
George A. Miller. 1995 · 1995
Earlier work this paper cites.
A primer of probability logic
Ernest Wilcox Adams. 1996 · 1996
Earlier work this paper cites.
Semiring-based csps and valued csps: Frameworks, properties, and comparison
Stefano Bistarelli, Ugo Montanari, Francesca Rossi, Thomas Schiex, Gérard Verfaillie, and Hélene Fargier. 1999 · 1999
Earlier work this paper cites.
Handbook of Constraint Programming
Francesca Rossi, Peter van Beek, and Toby Walsh. 2006 · 2006
Earlier work this paper cites.
The sparql query graph model for query optimization
Olaf Hartig and Ralf Heese. 2007 · 2007
Earlier work this paper cites.
Yago: a core of semantic knowledge
Fabian M Suchanek, Gjergji Kasneci, and Gerhard Weikum. 2007 · 2007
Earlier work this paper cites.
Learning to rank for information retrieval
Tie-Yan Liu et al. 2009 · 2009
Earlier work this paper cites.
Toward an architecture for never-ending language learning
Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, Estevam Hruschka, and Tom Mitchell. 2010 · 2010
Earlier work this paper cites.
Exact and inexact graph matching: Methodology and applications
Kaspar Riesen, Xiaoyi Jiang, and Horst Bunke. 2010 · 2010
Earlier work this paper cites.
Translating Embeddings for Modeling Multi-relational Data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Earlier work this paper cites.
Wikidata: a free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch. 2014 · 2014
Earlier work this paper cites.
Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng. 2015 · 2015
Cited alongside, same era.
Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Embedding logical queries on knowledge graphs
Will Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, and Jure Leskovec. 2018 · 2018
Cited alongside, same era.
Embedding uncertain knowledge graphs
Xuelu Chen, Muhao Chen, Weijia Shi, Yizhou Sun, and Carlo Zaniolo. 2019 · 2019
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Query2box: Reasoning Over Knowledge Graphs In Vector Space Using Box Embeddings
Benchmarking the Combinatorial Generalizability of Complex Query Answering on Knowledge Graphs
Zihao Wang, Hang Yin, and Yangqiu Song. 2021 · 2021
Later among the works it cites.
Cone: Cone embeddings for multi-hop reasoning over knowledge graphs
Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, and Feng Wu. 2021 · 2021
Later among the works it cites.
Query2Particles: Knowledge Graph Reasoning with Particle Embeddings
Jiaxin Bai, Zihao Wang, Hongming Zhang, and Yangqiu Song. 2022 · 2022
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Fuzzy logic based logical query answering on knowledge graphs
Xuelu Chen, Ziniu Hu, and Yizhou Sun. 2022 · 2022
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Probabilistic databases
Dan Suciu, Dan Olteanu, Christopher Ré, and Christoph Koch. 2022 · 2022
Later among the works it cites.
Neural-Symbolic Models for Logical Queries on Knowledge Graphs
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H Ren, W Hu, and J Leskovec. 2020 · 2020
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Beta embeddings for multi-hop logical reasoning in knowledge graphs
Hongyu Ren and Jure Leskovec. 2020 · 2020
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Aser: A large-scale eventuality knowledge graph
Hongming Zhang, Xin Liu, Haojie Pan, Yangqiu Song, and Cane Wing-Ki Leung. 2020 · 2020
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Neural Methods for Logical Reasoning over Knowledge Graphs
Alfonso Amayuelas, Shuai Zhang, Xi Susie Rao, and Ce Zhang. 2021 · 2021
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Complex Query Answering with Neural Link Predictors
Erik Arakelyan, Daniel Daza, Pasquale Minervini, and Michael Cochez. 2021 · 2021
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Open-world probabilistic databases: Semantics, algorithms, complexity
Ismail Ilkan Ceylan, Adnan Darwiche, and Guy Van den Broeck. 2021 · 2021
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Probabilistic entity representation model for reasoning over knowledge graphs
Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, and Chandan Reddy. 2021 · 2021
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Zhaocheng Zhu, Mikhail Galkin, Zuobai Zhang, and Jian Tang. 2022 · 2022
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Adapting Neural Link Predictors for Complex Query Answering
Erik Arakelyan, Pasquale Minervini, and Isabelle Augenstein. 2023 · 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 · 2023
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Learning Language Representations with Logical Inductive Bias
Jianshu Chen. 2023 · 2023
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Knowledge graph embedding based on graph neural network
Shuang Liang. 2023 · 2023
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Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases
Hongyu Ren, Mikhail Galkin, Michael Cochez, Zhaocheng Zhu, and Jure Leskovec. 2023 · 2023
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The string database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest
Damian Szklarczyk, Rebecca Kirsch, Mikaela Koutrouli, Katerina Nastou, Farrokh Mehryary, Radja Hachilif, Annika L Gable, Tao Fang, Nadezhda T Doncheva, Sampo Pyysalo, et al. 2023 · 2023
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Rethinking existential first order queries and their inference on knowledge graphs
Hang Yin, Zihao Wang, and Yangqiu Song. 2024 · 2024
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard. 2016 · 2080
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