mlsanityData to 14 Oct 2026

Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs

arXiv 1811.01118 ↗First posted 2 Nov 2018cs.LG cs.AI stat.MLcited by 17

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Abstract (arXiv)

In this paper, we conduct an empirical investigation of neural query graph ranking approaches for the task of complex question answering over knowledge graphs. We experiment with six different ranking models and propose a novel self-attention based slot matching model which exploits the inherent structure of query graphs, our logical form of choice. Our proposed model generally outperforms the other models on two QA datasets over the DBpedia knowledge graph, evaluated in different settings. In addition, we show that transfer learning from the larger of those QA datasets to the smaller dataset yields substantial improvements, effectively offsetting the general lack of training data.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). First posted on arXiv 2 Nov 2018.

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Citing papers per year: 2021: 9; 2022: 5; 2023: 2; 2024: 1.

17 papers.

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  1. 2021A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutionscited by 78
  2. 2021Complex Knowledge Base Question Answering: A Surveycited by 52
  3. 2021Formal Query Building with Query Structure Prediction for Complex Question Answering over Knowledge Basecited by 16
  4. 2021Outlining and Filling: Hierarchical Query Graph Generation for Answering Complex Questions over Knowledge Graphscited by 16
  5. 2021A Two-Stage Approach towards Generalization in Knowledge Base Question Answeringcited by 15
  6. 2021Generative Relation Linking for Question Answering over Knowledge Basescited by 14
  7. 2022Knowledge Graph Question Answering Leaderboard: A Community Resource to Prevent a Replication Crisiscited by 14
  8. 2022Semantic Structure based Query Graph Prediction for Question Answering over Knowledge Graphcited by 9
  9. 2024Multi-hop Question Answering over Knowledge Graphs using Large Language Modelscited by 6
  10. 2023Knowledge Graph Question Answering for Materials Science (KGQA4MAT): Developing Natural Language Interface for Metal-Organic Frameworks Knowledge Graph (MOF-KG) Using LLMcited by 5
  11. 2021Modeling Global Semantics for Question Answering over Knowledge Basescited by 3
  12. 2022Targeted Extraction of Temporal Facts from Textual Resources for Improved Temporal Question Answering over Knowledge Basescited by 3
5 more
  1. 2022Contrastive Representation Learning for Conversational Question Answering over Knowledge Graphscited by 2
  2. 2021Knowledge Graph Question Answering via SPARQL Silhouette Generationcited by 1
  3. 2022Improving Complex Knowledge Base Question Answering via Question-to-Action and Question-to-Question Alignmentcited by 1
  4. 2023Semantic Parsing for Question Answering over Knowledge Graphscited by 1
  5. 2021Few-shot Multi-hop Question Answering over Knowledge Basecited by 0