Discovering underground roads from trajectories without road network

Qiuge Song; Jiali Mao; Cheqing Jin

doi:10.1007/978-3-319-39937-9_11

Discovering underground roads from trajectories without road network

Qiuge Song
, Jiali Mao
, Cheqing Jin^*

^*Corresponding author for this work

School of Data Science and Engineering

East China Normal University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

With the wide application of GPS-enabled electronic devices, huge amounts of positional information data have been accumulated, so that it’s critical to discover inherent knowledge from such massive data. In this paper, we address this topic by proposing two issues, including how to discover the underpasses for pedestrians to cross the roads, and how to discover the tunnels providing passageways for vehicles. Subsequently, we propose a three-step framework to deal with the issues, including an incremental clustering phase, a sub-trajectory detecting phase and a cluster filtering phase. Experiments upon real-life data sets demonstrate the effectiveness and efficiency of the proposed framework.

Original language	English
Title of host publication	Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings
Editors	Jianliang Xu, Nan Zhang, Dexi Liu, Bin Cui, Xiang Lian
Publisher	Springer Verlag
Pages	137-150
Number of pages	14
ISBN (Print)	9783319399362
DOIs	https://doi.org/10.1007/978-3-319-39937-9_11
State	Published - 2016
Event	17th International Conference on Web-Age Information Management, WAIM 2016 - Nanchang, China Duration: 3 Jun 2016 → 5 Jun 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9658
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th International Conference on Web-Age Information Management, WAIM 2016
Country/Territory	China
City	Nanchang
Period	3/06/16 → 5/06/16

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10.1007/978-3-319-39937-9_11

Cite this

Song, Q., Mao, J., & Jin, C. (2016). Discovering underground roads from trajectories without road network. In J. Xu, N. Zhang, D. Liu, B. Cui, & X. Lian (Eds.), Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings (pp. 137-150). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9658). Springer Verlag. https://doi.org/10.1007/978-3-319-39937-9_11

Song, Qiuge ; Mao, Jiali ; Jin, Cheqing. / Discovering underground roads from trajectories without road network. Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings. editor / Jianliang Xu ; Nan Zhang ; Dexi Liu ; Bin Cui ; Xiang Lian. Springer Verlag, 2016. pp. 137-150 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{a745f71a33a34a1b80c1884156b84ba6,

title = "Discovering underground roads from trajectories without road network",

abstract = "With the wide application of GPS-enabled electronic devices, huge amounts of positional information data have been accumulated, so that it{\textquoteright}s critical to discover inherent knowledge from such massive data. In this paper, we address this topic by proposing two issues, including how to discover the underpasses for pedestrians to cross the roads, and how to discover the tunnels providing passageways for vehicles. Subsequently, we propose a three-step framework to deal with the issues, including an incremental clustering phase, a sub-trajectory detecting phase and a cluster filtering phase. Experiments upon real-life data sets demonstrate the effectiveness and efficiency of the proposed framework.",

author = "Qiuge Song and Jiali Mao and Cheqing Jin",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 17th International Conference on Web-Age Information Management, WAIM 2016 ; Conference date: 03-06-2016 Through 05-06-2016",

year = "2016",

doi = "10.1007/978-3-319-39937-9\_11",

language = "英语",

isbn = "9783319399362",

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

publisher = "Springer Verlag",

pages = "137--150",

editor = "Jianliang Xu and Nan Zhang and Dexi Liu and Bin Cui and Xiang Lian",

booktitle = "Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings",

address = "德国",

}

Song, Q, Mao, J & Jin, C 2016, Discovering underground roads from trajectories without road network. in J Xu, N Zhang, D Liu, B Cui & X Lian (eds), Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9658, Springer Verlag, pp. 137-150, 17th International Conference on Web-Age Information Management, WAIM 2016, Nanchang, China, 3/06/16. https://doi.org/10.1007/978-3-319-39937-9_11

Discovering underground roads from trajectories without road network. / Song, Qiuge; Mao, Jiali ; Jin, Cheqing.
Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings. ed. / Jianliang Xu; Nan Zhang; Dexi Liu; Bin Cui; Xiang Lian. Springer Verlag, 2016. p. 137-150 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9658).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Song, Qiuge

AU - Mao, Jiali

AU - Jin, Cheqing

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2016.

PY - 2016

Y1 - 2016

N2 - With the wide application of GPS-enabled electronic devices, huge amounts of positional information data have been accumulated, so that it’s critical to discover inherent knowledge from such massive data. In this paper, we address this topic by proposing two issues, including how to discover the underpasses for pedestrians to cross the roads, and how to discover the tunnels providing passageways for vehicles. Subsequently, we propose a three-step framework to deal with the issues, including an incremental clustering phase, a sub-trajectory detecting phase and a cluster filtering phase. Experiments upon real-life data sets demonstrate the effectiveness and efficiency of the proposed framework.

AB - With the wide application of GPS-enabled electronic devices, huge amounts of positional information data have been accumulated, so that it’s critical to discover inherent knowledge from such massive data. In this paper, we address this topic by proposing two issues, including how to discover the underpasses for pedestrians to cross the roads, and how to discover the tunnels providing passageways for vehicles. Subsequently, we propose a three-step framework to deal with the issues, including an incremental clustering phase, a sub-trajectory detecting phase and a cluster filtering phase. Experiments upon real-life data sets demonstrate the effectiveness and efficiency of the proposed framework.

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DO - 10.1007/978-3-319-39937-9_11

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AN - SCOPUS:84976635968

SN - 9783319399362

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

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EP - 150

BT - Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings

A2 - Xu, Jianliang

A2 - Zhang, Nan

A2 - Liu, Dexi

A2 - Cui, Bin

A2 - Lian, Xiang

PB - Springer Verlag

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Song Q, Mao J , Jin C. Discovering underground roads from trajectories without road network. In Xu J, Zhang N, Liu D, Cui B, Lian X, editors, Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings. Springer Verlag. 2016. p. 137-150. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-39937-9_11

Discovering underground roads from trajectories without road network

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