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)
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Authors
- 1. Zhijie Zhang (Fudan University)
- 2. Weiguo Zheng (Fudan University)
BibTeX Citation
@inproceedings{zhang_sigmod26,
title = {{BEE: Towards Redundancy Reduction via Block-Separator Decomposition for Subgraph Matching}},
author = {Zhang, Zhijie and Zheng, Weiguo},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3749159},
url = {https://dl.acm.org/doi/10.1145/3749159},
year = {2026}
}Incoming Citations (Sorted by Pagerank)
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,558 | Characterizing Parallel Subgraph Matching Performance: A Systematic Study of Interactions, Scalability, and Enumeration | 2026 | VLDB | 5.093636e-05 |
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