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BEE: Towards Redundancy Reduction via Block-Separator Decomposition for Subgraph Matching
Summary: BEE uses block-separator decomposition to cut redundancy in subgraph matching, enabling detection of global and partial redundancies beyond local pruning. It proves NP-hardness of optimizing the block-separator tree, and offers greedy decomposition plus a block-reference structure that deliver large EPS speedups over state-of-the-art.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 7316
- Venue
- SIGMOD
- Year
- 2026
- Pagerank
- 4.1945683e-05
- Overall Rank
- 10,014 | 30.34%
- DOI
-
10.1145/3749159
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Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 26 of 26 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 331 |
The Ubiquity of Large Graphs and Surprising Challenges of Graph Processing |
2018 |
VLDB |
0.00027214222 |
| 342 |
EmptyHeaded: A Relational Engine for Graph Processing |
2016 |
SIGMOD |
0.00026795977 |
| 461 |
Graphs-at-a-time: Query Language and Access Methods for Graph Databases |
2008 |
SIGMOD |
0.00022499343 |
| 764 |
TurboISO: Towards UltraFast and Robust Subgraph Isomorphism Search in Large Graph Databases |
2013 |
SIGMOD |
0.00017018712 |
| 1,180 |
Efficient Subgraph Matching by Postponing Cartesian Products |
2016 |
SIGMOD |
0.00013456907 |
| 1,561 |
Efficient Subgraph Matching: Harmonizing Dynamic Programming, Adaptive Matching Order, and Failing Set Together |
2019 |
SIGMOD |
0.00011358946 |
| 1,703 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010836769 |
| 1,756 |
Graphflow: An Active Graph Database |
2017 |
SIGMOD |
0.00010664542 |
| 1,775 |
CECI: Compact Embedding Cluster Index for Scalable Subgraph Matching |
2019 |
SIGMOD |
0.00010602927 |
| 1,924 |
In-Memory Subgraph Matching: An In-depth Study |
2020 |
SIGMOD |
0.00010077055 |
| 2,162 |
Scalable Subgraph Enumeration in MapReduce |
2015 |
VLDB |
9.3964337e-05 |
| 2,409 |
TreeSpan: Efficiently Computing Similarity All-Matching |
2012 |
SIGMOD |
8.8776858e-05 |
| 2,801 |
Scalable Distributed Subgraph Enumeration |
2017 |
VLDB |
8.0992955e-05 |
| 2,910 |
DUALSIM: Parallel Subgraph Enumeration in a Massive Graph on a Single Machine |
2016 |
SIGMOD |
7.9266529e-05 |
| 2,997 |
Subgraph Matching: on Compression and Computation |
2018 |
VLDB |
7.7559339e-05 |
| 3,036 |
RapidMatch: A Holistic Approach to Subgraph Query Processing |
2021 |
VLDB |
7.6735171e-05 |
| 3,187 |
Versatile Equivalences: Speeding up Subgraph Query Processing and Subgraph Matching |
2021 |
SIGMOD |
7.4136521e-05 |
| 3,266 |
Learned Cardinality Estimation: An In-depth Study |
2022 |
SIGMOD |
7.3074684e-05 |
| 3,646 |
G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching |
2020 |
SIGMOD |
6.8853079e-05 |
| 4,470 |
GuP: Fast Subgraph Matching by Guard-based Pruning |
2023 |
SIGMOD |
6.1557462e-05 |
| 5,009 |
HUGE: An Efficient and Scalable Subgraph Enumeration System |
2021 |
SIGMOD |
5.761237e-05 |
| 5,728 |
Circinus: Fast Redundancy-Reduced Subgraph Matching |
2023 |
SIGMOD |
5.3507988e-05 |
| 6,281 |
A Comprehensive Survey and Experimental Study of Subgraph Matching: Trends, Unbiasedness, and Interaction |
2024 |
SIGMOD |
5.128862e-05 |
| 6,575 |
Fast Continuous Subgraph Matching over Streaming Graphs via Backtracking Reduction |
2023 |
SIGMOD |
5.0052259e-05 |
| 7,100 |
BICE: Exploring Compact Search Space by Using Bipartite Matching and Cell-Wide Verification |
2023 |
VLDB |
4.8326259e-05 |
| 7,221 |
Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation |
2023 |
SIGMOD |
4.797194e-05 |
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VLDB |
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