Efficient Top-k Algorithms for Approximate Substring Matching
Summary: Proposes top-k approximate substring matching over long strings under edit-distance with containment search. It uses novel filtering based on q-grams and inverted q-gram indexes to prune distance computations, achieving scalable, efficient performance on real datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Younghoon Kim
- 2. Kyuseok Shim
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,936 | Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning | 2020 | VLDB | 5.2654071e-05 |
| 6,726 | A Pivotal Prefix Based Filtering Algorithm for String Similarity Search | 2014 | SIGMOD | 4.9484027e-05 |
| 7,474 | Cardinality Estimation of Approximate Substring Queries using Deep Learning | 2022 | VLDB | 4.7194345e-05 |
| 9,726 | Cardinality Estimation of LIKE Predicate Queries using Deep Learning | 2025 | SIGMOD | 4.2943379e-05 |
| 10,216 | The Case For Language Model Approximated LIKE Predicate | 2026 | SIGMOD | 4.1945683e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next