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A Learned Sketch for Subgraph Counting

Summary: Active Learned Sketch for Subgraph Counting (ALSS) fuses a neural regression sketch with an active-learning loop to update on new query graphs. Targets large labeled graphs, enabling accurate, scalable subgraph counting and aiding optimizers for multi-way self-joins. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h6be0d606dc1bc100
Venue
SIGMOD
Year
2021
Pagerank
7.5771609e-05
Overall Rank
3,161 | 78.76%
DOI
10.1145/3448016.3457289

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhao_sigmod21,
        title = {{A Learned Sketch for Subgraph Counting}},
        author = {Zhao, Kangfei and Yu, Jeffrey Xu and Zhang, Hao and Li, Qiyan and Rong, Yu},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3457289},
        url = {https://dl.acm.org/doi/10.1145/3448016.3457289},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 20 of 20 citing papers.

Rank Citing Paper Year Venue Pagerank
2,635 Neural Subgraph Counting with Wasserstein Estimator 2022 SIGMOD 8.1954989e-05
2,941 Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed 2022 VLDB 7.8297732e-05
3,453 Computing Graph Edit Distance via Neural Graph Matching 2023 VLDB 7.287012e-05
4,459 Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process 2022 SIGMOD 6.5883555e-05
5,426 Cardinality Estimation of Subgraph Matching: A Filtering-Sampling Approach 2024 VLDB 6.1332147e-05
6,472 Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks 2024 SIGMOD 5.7716301e-05
7,535 Fast Local Subgraph Counting 2024 VLDB 5.4983904e-05
7,878 Double-Anonymous Sketch: Achieving Top-K-fairness for Finding Global Top-K Frequent Items 2023 SIGMOD 5.4332155e-05
8,237 Computing Approximate Graph Edit Distance via Optimal Transport 2025 SIGMOD 5.3697463e-05
8,337 Machine Learning for Subgraph Extraction: Methods, Applications and Challenges 2023 VLDB 5.3502656e-05
8,484 TreeSensing: Linearly Compressing Sketches with Flexibility 2023 SIGMOD 5.330748e-05
9,657 gSWORD: GPU-accelerated Sampling for Subgraph Counting 2024 SIGMOD 5.142891e-05
9,804 NeuSO: Neural Optimizer for Subgraph Queries 2026 SIGMOD 5.1233734e-05
9,968 Inductive Attributed Community Search: to Learn Communities across Graphs 2024 VLDB 5.1014161e-05
10,062 SPACE: Cardinality Estimation for Path Queries Using Cardinality-Aware Sequence-based Learning 2025 SIGMOD 5.0851868e-05
10,187 Path-centric Cardinality Estimation for Subgraph Matching 2025 VLDB 5.0628015e-05
10,651 Enumerating Graph Pattern Matches with ML Oracles 2026 SIGMOD 4.9769913e-05
10,891 Efficient GPU-Accelerated Local Subgraph Counting 2026 VLDB 4.9769913e-05
11,287 Efficient and Adaptive Estimation of Local Triadic Coefficients 2025 VLDB 4.9769913e-05
11,294 Efficient and Accurate Subgraph Counting: A Bottom-up Flow-learning Based Approach 2025 VLDB 4.9769913e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 29 of 29 cited papers.

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

Rank Cited Paper Year Venue Pagerank
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061067652
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035876108
208 EmptyHeaded: A Relational Engine for Graph Processing 2016 SIGMOD 0.00024899872
289 Graphs-at-a-time: Query Language and Access Methods for Graph Databases 2008 SIGMOD 0.00021960834
315 Worst-Case Optimal Join Algorithms: Techniques, Results, and Open Problems 2018 PODS 0.00021236408
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021166957
406 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019050182
438 Taming Verification Hardness: An Efficient Algorithm for Testing Subgraph Isomorphism 2008 VLDB 0.00018278591
462 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017836105
596 Wander Join: Online Aggregation via Random Walks 2016 SIGMOD 0.00015782051
659 Efficient Subgraph Matching by Postponing Cartesian Products 2016 SIGMOD 0.00015048943
691 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014737455
713 Optimizing Subgraph Queries by Combining Binary and Worst-Case Optimal Joins 2019 VLDB 0.00014571507
749 Join Size Estimation Subject to Filter Conditions 2015 VLDB 0.00014261044
795 Random Sampling over Joins Revisited 2018 SIGMOD 0.00013934719
819 Hypertree Decompositions: Questions and Answers 2016 PODS 0.00013660715
961 Efficient Subgraph Matching: Harmonizing Dynamic Programming, Adaptive Matching Order, and Failing Set Together 2019 SIGMOD 0.00012830477
1,091 What do Shannon-type Inequalities, Submodular Width, and Disjunctive Datalog have to do with one another? 2017 PODS 0.00012068611
1,100 CECI: Compact Embedding Cluster Index for Scalable Subgraph Matching 2019 SIGMOD 0.00012007739
1,180 In-Memory Subgraph Matching: An In-depth Study 2020 SIGMOD 0.00011622165
1,252 Distributed Evaluation of Subgraph Queries Using Worst-case Optimal Low-Memory Dataflows 2018 VLDB 0.00011334813
1,465 Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities 2019 SIGMOD 0.00010572023
1,580 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010177136
1,828 DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models 2019 SIGMOD 9.547768e-05
1,836 Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank 2020 VLDB 9.53235e-05
2,217 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 8.8151982e-05
2,278 Active Learning for ML Enhanced Database Systems 2020 SIGMOD 8.7057608e-05
2,824 G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching 2020 SIGMOD 7.9662478e-05
2,987 Motivo: fast motif counting via succinct color coding and adaptive sampling 2019 VLDB 7.777194e-05
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