Does preprocessing help in fast sequence comparisons?
Elazar Goldenberg, Aviad Rubinstein, Barna Saha
摘要
We study edit distance computation with preprocessing: the preprocessing algorithm acts on each string separately, and then the query algorithm takes as input the two preprocessed strings. This model is inspired by scenarios where we would like to compute edit distance between many pairs in the same pool of strings. Our results include: Permutation-LCS If the LCS between two permutations has length nk, we can compute it exactly with O(n log(n)) preprocessing and O(k log(n)) query time. Small edit distance For general strings, if their edit distance is at most k, we can compute it exactly with O(n log(n)) preprocessing and O(k 2 log(n)) query time. Approximate edit distance For the most general input, we can approximate the edit distance to within factor (7+o(1)) with preprocessing time Õ(n 2 ) and query time Õ(n 1.5+o(1) ). All of these results significantly improve over the state of the art in edit distance computation without preprocessing. Interestingly, by combining ideas from our algorithms with preprocessing, we provide new improved results for approximating edit distance without preprocessing in subquadratic time.
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引用它的顶会 Paper14
- Edit Distance in Near-Linear Time: it's a Constant FactorAlexandr Andoni, Negev Shekel NosatzkiFOCS 2020 · 被引用 28 次
- Sublinear-Time Algorithms for Computing & Embedding Gap Edit DistanceTomasz Kociumaka, Barna SahaFOCS 2020 · 被引用 9 次
- Near-Optimal Quantum Algorithms for Bounded Edit Distance and Lempel-Ziv FactorizationDaniel Gibney, Ce Jin, Tomasz Kociumaka, Sharma V. ThankachanSODA 2024 · 被引用 7 次
- How Compression and Approximation Affect Efficiency in String Distance MeasuresArun Ganesh, Tomasz Kociumaka, Andrea Lincoln, Barna SahaSODA 2022 · 被引用 7 次
- Gap Edit Distance via Non-Adaptive Queries: Simple and OptimalElazar Goldenberg, Tomasz Kociumaka, Robert Krauthgamer, Barna SahaFOCS 2022 · 被引用 5 次
它引用的顶会 Paper3
- Reducing approximate Longest Common Subsequence to approximate Edit DistanceAviad Rubinstein, Zhao SongSODA 2020 · 被引用 24 次
- Constant factor approximations to edit distance on far input pairs in nearly linear timeMichal Koucký, Michael E. SaksSTOC 2020 · 被引用 5 次
- Constant-factor approximation of near-linear edit distance in near-linear timeJoshua Brakensiek, Aviad RubinsteinSTOC 2020 · 被引用 1 次
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