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Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders

arXiv 2004.02596 ↗First posted 6 Apr 2020cs.AI cs.LGcited by 28

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Abstract (arXiv)

Representation learning for knowledge graphs (KGs) has focused on the problem of answering simple link prediction queries. In this work we address the more ambitious challenge of predicting the answers of conjunctive queries with multiple missing entities. We propose Bi-Directional Query Embedding (BIQE), a method that embeds conjunctive queries with models based on bi-directional attention mechanisms. Contrary to prior work, bidirectional self-attention can capture interactions among all the elements of a query graph. We introduce a new dataset for predicting the answer of conjunctive query and conduct experiments that show BIQE significantly outperforming state of the art baselines.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Apr 2020.

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Citing papers per year: 2021: 3; 2022: 7; 2023: 9; 2024: 7; 2025: 2.

28 papers.

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  1. 2022Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queriescited by 39
  2. 2023Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databasescited by 35
  3. 2022Inductive Logical Query Answering in Knowledge Graphscited by 25
  4. 2021Query Embedding on Hyper-relational Knowledge Graphscited by 23
  5. 2022Transformers over Directed Acyclic Graphscited by 23
  6. 2021Benchmarking the Combinatorial Generalizability of Complex Query Answering on Knowledge Graphscited by 21
  7. 2022GammaE: Gamma Embeddings for Logical Queries on Knowledge Graphscited by 21
  8. 2022Knowledge Graph Reasoning with Logics and Embeddings: Survey and Perspectivecited by 18
  9. 2021SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphscited by 17
  10. 2023Wasserstein-Fisher-Rao Embedding: Logical Query Embeddings with Local Comparison and Global Transportcited by 16
  11. 2022A Unified Framework for Rank-based Evaluation Metrics for Link Prediction in Knowledge Graphscited by 14
  12. 2023Sequential Query Encoding For Complex Query Answering on Knowledge Graphscited by 13
16 more
  1. 2023Knowledge Graph Reasoning over Entities and Numerical Valuescited by 11
  2. 2022NQE: N-ary Query Embedding for Complex Query Answering over Hyper-Relational Knowledge Graphscited by 9
  3. 2024Effective Instruction Parsing Plugin for Complex Logical Query Answering on Knowledge Graphscited by 8
  4. 2025Enhancing Transformers for Generalizable First-Order Logical Entailmentcited by 6
  5. 2023Privacy-Preserved Neural Graph Databasescited by 5
  6. 2024Conditional Logical Message Passing Transformer for Complex Query Answeringcited by 5
  7. 2024Generating SROI^- Ontologies via Knowledge Graph Query Embedding Learningcited by 5
  8. 2023A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphscited by 4
  9. 2024Learning Federated Neural Graph Databases for Answering Complex Queries from Distributed Knowledge Graphscited by 4
  10. 2024DAGE: DAG Query Answering via Relational Combinator with Logical Constraintscited by 4
  11. 2023Query Structure Modeling for Inductive Logical Reasoning Over Knowledge Graphscited by 3
  12. 2023Modeling Relational Patterns for Logical Query Answering over Knowledge Graphscited by 2
  13. 2025NN-Former: Rethinking Graph Structure in Neural Architecture Representationcited by 2
  14. 2024Pathformer: Recursive Path Query Encoding for Complex Logical Query Answeringcited by 1
  15. 2023Approximate Answering of Graph Queriescited by 0
  16. 2024Prompt-fused framework for Inductive Logical Query Answeringcited by 0