Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series
| dc.contributor.author | Froese, Vincent | |
| dc.contributor.author | Jain, Brijnesh | |
| dc.contributor.author | Rymar, Maciej | |
| dc.contributor.author | Weller, Mathias | |
| dc.date.accessioned | 2023-03-01T13:36:35Z | |
| dc.date.available | 2023-03-01T13:36:35Z | |
| dc.date.issued | 2022-09-22 | |
| dc.description.abstract | Dynamic Time Warping (DTW) is a well-known similarity measure for time series. The standard dynamic programming approach to compute the DTW distance of two length-n time series, however, requires O(n2) time, which is often too slow for real-world applications. Therefore, many heuristics have been proposed to speed up the DTW computation. These are often based on lower bounding techniques, approximating the DTW distance, or considering special input data such as binary or piecewise constant time series. In this paper, we present a first exact algorithm to compute the DTW distance of two run-length encoded time series whose running time only depends on the encoding lengths of the inputs. The worst-case running time is cubic in the encoding length. In experiments we show that our algorithm is indeed fast for time series with short encoding lengths. | en |
| dc.description.sponsorship | TU Berlin, Open-Access-Mittel – 2022 | |
| dc.identifier.eissn | 1432-0541 | |
| dc.identifier.issn | 0178-4617 | |
| dc.identifier.uri | https://depositonce.tu-berlin.de/handle/11303/18262 | |
| dc.identifier.uri | https://doi.org/10.14279/depositonce-17055 | |
| dc.language.iso | en | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.ddc | 510 Mathematik | de |
| dc.subject.other | time series similarity | en |
| dc.subject.other | sparse data | en |
| dc.subject.other | block matrix | en |
| dc.subject.other | line intersections | en |
| dc.title | Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series | en |
| dc.type | Article | |
| dc.type.version | publishedVersion | |
| dcterms.bibliographicCitation.doi | 10.1007/s00453-022-01038-3 | |
| dcterms.bibliographicCitation.journaltitle | Algorithmica | |
| dcterms.bibliographicCitation.originalpublishername | Springer Nature | |
| dcterms.bibliographicCitation.originalpublisherplace | Heidelberg | |
| dcterms.bibliographicCitation.pageend | 508 | |
| dcterms.bibliographicCitation.pagestart | 492 | |
| dcterms.bibliographicCitation.volume | 85 | |
| dcterms.rightsHolder.reference | Creative-Commons-Lizenz | |
| tub.accessrights.dnb | free | |
| tub.affiliation | Fak. 4 Elektrotechnik und Informatik::Inst. Softwaretechnik und Theoretische Informatik::FG Algorithmik und Komplexitätstheorie | |
| tub.publisher.universityorinstitution | Technische Universität Berlin |