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DOI: 10.4230/LIPIcs.ISAAC.2019.23
URN: urn:nbn:de:0030-drops-115195
URL: https://drops.dagstuhl.de/opus/volltexte/2019/11519/
Fox, Kyle ; Li, Xinyi
Approximating the Geometric Edit Distance
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Abstract
Edit distance is a measurement of similarity between two sequences such as strings, point sequences, or polygonal curves. Many matching problems from a variety of areas, such as signal analysis, bioinformatics, etc., need to be solved in a geometric space. Therefore, the geometric edit distance (GED) has been studied. In this paper, we describe the first strictly sublinear approximate near-linear time algorithm for computing the GED of two point sequences in constant dimensional Euclidean space. Specifically, we present a randomized O(n log^2n) time O(sqrt n)-approximation algorithm. Then, we generalize our result to give a randomized alpha-approximation algorithm for any alpha in [1, sqrt n], running in time O~(n^2/alpha^2). Both algorithms are Monte Carlo and return approximately optimal solutions with high probability.
BibTeX - Entry
@InProceedings{fox_et_al:LIPIcs:2019:11519,
author = {Kyle Fox and Xinyi Li},
title = {{Approximating the Geometric Edit Distance}},
booktitle = {30th International Symposium on Algorithms and Computation (ISAAC 2019)},
pages = {23:1--23:16},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-130-6},
ISSN = {1868-8969},
year = {2019},
volume = {149},
editor = {Pinyan Lu and Guochuan Zhang},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2019/11519},
URN = {urn:nbn:de:0030-drops-115195},
doi = {10.4230/LIPIcs.ISAAC.2019.23},
annote = {Keywords: Geometric edit distance, Approximation, Randomized algorithms}
}
| Keywords: | Geometric edit distance, Approximation, Randomized algorithms | |
| Seminar: | 30th International Symposium on Algorithms and Computation (ISAAC 2019) | |
| Issue date: | 2019 | |
| Date of publication: | 28.11.2019 |
