Trajectory set similarity measure: An EMD-based approach

Dan He*, Boyu Ruan, Bolong Zheng, Xiaofang Zhou

*Kontaktforfatter

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

3 Citationer (Scopus)

Abstract

To address the trajectory sparsity issue concerning Origin-Destination (OD) pairs, in general, most existing studies strive to reconstruct trajectories by concatenating the sub-trajectories along the specific paths and filling up the sparsity with conceptual trajectories. However, none of them gives the robustness validation for their reconstructed trajectories. By intuition, the reconstructed trajectories are more qualified if they are more similar to the exact ones traversing directly from the origin to the destination, which indicates the effectiveness of the corresponding trajectory augmentation algorithms. Nevertheless, to our knowledge, no existing work has studied the similarity of trajectory sets. Motivated by this, we propose a novel similarity measure to evaluate the similarity between two set of trajectories, borrowing the idea of the Earth Mover’s Distance. Empirical studies on a large real trajectory dataset show that our proposed similarity measure is effective and robust.

OriginalsprogEngelsk
TitelDatabases Theory and Applications : 29th Australasian Database Conference, ADC 2018, Proceedings
Antal sider13
ForlagSpringer
Publikationsdato1 jan. 2018
Sider28-40
ISBN (Trykt)978-3-319-92012-2
ISBN (Elektronisk)978-3-319-92013-9
DOI
StatusUdgivet - 1 jan. 2018
Begivenhed29th Australasian Database Conference, ADC 2018 - Gold Coast, Australien
Varighed: 24 maj 201827 maj 2018

Konference

Konference29th Australasian Database Conference, ADC 2018
Land/OmrådeAustralien
ByGold Coast
Periode24/05/201827/05/2018
NavnLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Vol/bind10837 LNCS
ISSN0302-9743

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