Cardinality Estimation of Approximate Substring Queries using Deep Learning
Summary: DL-based cardinality estimation for approximate substring queries, outperforming traditional summaries. Introduces efficient train-data generation with shared computations and a novel learning method for fast, accurate training; experiments show clear gains over baselines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Suyong Kwon
- 2. Woohwan Jung
- 3. Kyuseok Shim
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,186 | LPLM: A Neural Language Model for Cardinality Estimation of LIKE-Queries | 2024 | SIGMOD | 4.8063731e-05 |
| 9,402 | CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models | 2024 | SIGMOD | 4.3441378e-05 |
| 9,408 | Experimental Analysis of Large-scale Learnable Vector Storage Compression | 2024 | VLDB | 4.3441378e-05 |
| 9,726 | Cardinality Estimation of LIKE Predicate Queries using Deep Learning | 2025 | SIGMOD | 4.2943379e-05 |
| 9,945 | SSCard: Substring Cardinality Estimation using Suffix Tree-Guided Learned FM-Index | 2026 | SIGMOD | 4.2432653e-05 |
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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.
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