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CECI: Compact Embedding Cluster Index for Scalable Subgraph Matching
Summary: CECI: Compact Embedding Cluster Index for scalable subgraph matching; partitions graph into embedding clusters. BFS pruning with rev-BFS refinement prune candidates; set-intersection replaces edge checks; cost-estimation guides clustering; 20.4x faster listing embeddings, 2.6x for 1,024.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 5618
- Venue
- SIGMOD
- Year
- 2019
- Pagerank
- 0.00010776518
- Overall Rank
- 1,715 | 88.09%
- DOI
-
10.1145/3299869.3300086
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 1 of 51 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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