Cardinality Estimation of LIKE Predicate Queries using Deep Learning
Summary: Deep-learning cardinality estimation for LIKE predicates via an N-gram table and conditional-regression head. LEADER generates shareable training data across related LIKE queries with a join-order strategy for fast, accurate estimates on real datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Suyong Kwon
- 2. Kyuseok Shim
- 3. Woohwan Jung
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,216 | The Case For Language Model Approximated LIKE Predicate | 2026 | SIGMOD | 4.1945683e-05 |
| 10,219 | Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking | 2026 | SIGMOD | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 21 of 21 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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