Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks

Summary: GNCE uses knowledge-graph embeddings and Graph Neural Networks to estimate conjunctive-query cardinalities. It outperforms sampling, summaries, and ML baselines, with inductive generalization to unseen entities and a compact parameter footprint. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6915
Venue: SIGMOD
Year: 2024
Pagerank: 5.9068986e-05
Overall Rank: 6,341 | 56.50%
DOI: 10.1145/3639299

Incoming Non-self Citations Over Time

Authors

1. Tim Schwabe (Ruhr University Bochum; Technical University of Munich)
2. Maribel Acosta (Technical University of Munich)

BibTeX Citation

@inproceedings{schwabe_sigmod24,
        title = {{Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks}},
        author = {Schwabe, Tim and Acosta, Maribel},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3639299},
        url = {https://dl.acm.org/doi/10.1145/3639299},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
9,617	NeuSO: Neural Optimizer for Subgraph Queries	2026	SIGMOD	5.2434488e-05
9,867	SPACE: Cardinality Estimation for Path Queries Using Cardinality-Aware Sequence-based Learning	2025	SIGMOD	5.2043672e-05
9,996	Path-centric Cardinality Estimation for Subgraph Matching	2025	VLDB	5.1814573e-05
10,374	GeoKGM: A Multimodal Large Language Model for Zero-Shot Knowledge Graph Completion in Geospatial Databases	2026	SIGMOD	5.093636e-05
10,452	Enumerating Graph Pattern Matches with ML Oracles	2026	SIGMOD	5.093636e-05
10,524	A Semantics-aware Approach for Graph Edit Distance Estimation over Knowledge Graphs	2026	VLDB	5.093636e-05
10,830	PlanRGCN: Predicting SPARQL Query Performance	2025	VLDB	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
84	Learned Cardinalities: Estimating Correlated Joins with Deep Learning	2019	CIDR	0.00035838391
280	Selectivity Estimation using Probabilistic Models	2001	SIGMOD	0.00022454217
323	DeepDB: Learn from Data, not from Queries!	2020	VLDB	0.00021264788
530	An Analytical Study of Large SPARQL Query Logs	2018	VLDB	0.0001709169
593	Wander Join: Online Aggregation via Random Walks	2016	SIGMOD	0.00016027871
737	Join Size Estimation Subject to Filter Conditions	2015	VLDB	0.00014490983
802	Random Sampling over Joins Revisited	2018	SIGMOD	0.00013907725
1,071	Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions	2011	VLDB	0.00012322342
2,723	Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation	2022	VLDB	8.2049453e-05
2,731	Neural Subgraph Counting with Wasserstein Estimator	2022	SIGMOD	8.1959181e-05
2,940	G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching	2020	SIGMOD	7.9381573e-05
3,283	A Learned Sketch for Subgraph Counting	2021	SIGMOD	7.56675e-05
4,368	Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process	2022	SIGMOD	6.7393882e-05

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