Spatio-temporal similarity measure algorithm for moving objects on spatial networks

Jae Woo Chang; Rabindra Bista; Young Chang Kim; Yong Ki Kim

doi:10.1007/978-3-540-74484-9_102

Spatio-temporal similarity measure algorithm for moving objects on spatial networks

Jae Woo Chang^*
, Rabindra Bista
, Young Chang Kim
, Yong Ki Kim

^*Corresponding author for this work

Jeonbuk National University

Research output: Contribution to conference › Conference paper › peer-review

28 Scopus citations

Abstract

In this paper, we propose a new spatio-temporal similarity measure to compute spatio-temporal relevance between two trajectories of moving objects on road networks, which is known as spatio-temporal distance (STDist). In addition, we provide a similar trajectory search algorithm to retrieve similar trajectories based on the proposed measure i.e., a combination of both spatial and temporal properties with respect to the motion of a given query trajectory. The performance evaluation shows that our approach outperforms the existing work in terms of searching similar trajectories of moving objects on road networks.

Original language	English
Title of host publication	Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings
Publisher	Springer Verlag
Pages	1165-1178
Number of pages	14
Edition	PART 3
ISBN (Print)	9783540744825
DOIs	https://doi.org/10.1007/978-3-540-74484-9_102
State	Published - 2007
Event	International Conference on Computational Science and its Applications, ICCSA 2007 - Kuala Lumpur, Malaysia Duration: 2007.08.26 → 2007.08.29

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	4707 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Computational Science and its Applications, ICCSA 2007
Country/Territory	Malaysia
City	Kuala Lumpur
Period	07.08.26 → 07.08.29

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities

Keywords

Addition-based approach
Algorithm
Multiplication-based approach
Spatio-temporal similarity

Quacquarelli Symonds(QS) Subject Topics

Computer Science & Information Systems

Access to Document

10.1007/978-3-540-74484-9_102

Cite this

Chang, J. W., Bista, R., Kim, Y. C., & Kim, Y. K. (2007). Spatio-temporal similarity measure algorithm for moving objects on spatial networks. In Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings (PART 3 ed., pp. 1165-1178). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4707 LNCS, No. PART 3). Springer Verlag. https://doi.org/10.1007/978-3-540-74484-9_102

Chang, Jae Woo ; Bista, Rabindra ; Kim, Young Chang et al. / Spatio-temporal similarity measure algorithm for moving objects on spatial networks. Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings. PART 3. ed. Springer Verlag, 2007. pp. 1165-1178 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

@inproceedings{fe08c29000e345508443b72674475845,

title = "Spatio-temporal similarity measure algorithm for moving objects on spatial networks",

abstract = "In this paper, we propose a new spatio-temporal similarity measure to compute spatio-temporal relevance between two trajectories of moving objects on road networks, which is known as spatio-temporal distance (STDist). In addition, we provide a similar trajectory search algorithm to retrieve similar trajectories based on the proposed measure i.e., a combination of both spatial and temporal properties with respect to the motion of a given query trajectory. The performance evaluation shows that our approach outperforms the existing work in terms of searching similar trajectories of moving objects on road networks.",

keywords = "Addition-based approach, Algorithm, Multiplication-based approach, Spatio-temporal similarity",

author = "Chang, \{Jae Woo\} and Rabindra Bista and Kim, \{Young Chang\} and Kim, \{Yong Ki\}",

year = "2007",

doi = "10.1007/978-3-540-74484-9\_102",

language = "English",

isbn = "9783540744825",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

number = "PART 3",

pages = "1165--1178",

booktitle = "Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings",

edition = "PART 3",

note = "International Conference on Computational Science and its Applications, ICCSA 2007 ; Conference date: 26-08-2007 Through 29-08-2007",

}

Chang, JW, Bista, R, Kim, YC & Kim, YK 2007, Spatio-temporal similarity measure algorithm for moving objects on spatial networks. in Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 4707 LNCS, Springer Verlag, pp. 1165-1178, International Conference on Computational Science and its Applications, ICCSA 2007, Kuala Lumpur, Malaysia, 07.08.26. https://doi.org/10.1007/978-3-540-74484-9_102

Spatio-temporal similarity measure algorithm for moving objects on spatial networks. / Chang, Jae Woo; Bista, Rabindra; Kim, Young Chang et al.
Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings. PART 3. ed. Springer Verlag, 2007. p. 1165-1178 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4707 LNCS, No. PART 3).

Research output: Contribution to conference › Conference paper › peer-review

TY - GEN

T1 - Spatio-temporal similarity measure algorithm for moving objects on spatial networks

AU - Chang, Jae Woo

AU - Bista, Rabindra

AU - Kim, Young Chang

AU - Kim, Yong Ki

PY - 2007

Y1 - 2007

N2 - In this paper, we propose a new spatio-temporal similarity measure to compute spatio-temporal relevance between two trajectories of moving objects on road networks, which is known as spatio-temporal distance (STDist). In addition, we provide a similar trajectory search algorithm to retrieve similar trajectories based on the proposed measure i.e., a combination of both spatial and temporal properties with respect to the motion of a given query trajectory. The performance evaluation shows that our approach outperforms the existing work in terms of searching similar trajectories of moving objects on road networks.

AB - In this paper, we propose a new spatio-temporal similarity measure to compute spatio-temporal relevance between two trajectories of moving objects on road networks, which is known as spatio-temporal distance (STDist). In addition, we provide a similar trajectory search algorithm to retrieve similar trajectories based on the proposed measure i.e., a combination of both spatial and temporal properties with respect to the motion of a given query trajectory. The performance evaluation shows that our approach outperforms the existing work in terms of searching similar trajectories of moving objects on road networks.

KW - Addition-based approach

KW - Algorithm

KW - Multiplication-based approach

KW - Spatio-temporal similarity

UR - https://www.scopus.com/pages/publications/38349020230

U2 - 10.1007/978-3-540-74484-9_102

DO - 10.1007/978-3-540-74484-9_102

M3 - Conference paper

AN - SCOPUS:38349020230

SN - 9783540744825

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 1165

EP - 1178

BT - Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings

PB - Springer Verlag

T2 - International Conference on Computational Science and its Applications, ICCSA 2007

Y2 - 26 August 2007 through 29 August 2007

ER -

Chang JW, Bista R, Kim YC, Kim YK. Spatio-temporal similarity measure algorithm for moving objects on spatial networks. In Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings. PART 3 ed. Springer Verlag. 2007. p. 1165-1178. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). doi: 10.1007/978-3-540-74484-9_102

Spatio-temporal similarity measure algorithm for moving objects on spatial networks

Abstract

Publication series

Conference

UN SDGs

Keywords

Quacquarelli Symonds(QS) Subject Topics

Access to Document

Other files and links

Fingerprint

Cite this