Human mobility-pattern discovery and next-place prediction from GPS data

Faina Khoroshevsky; Boaz Lerner

doi:10.1007/978-3-319-59259-6_3

Human mobility-pattern discovery and next-place prediction from GPS data

Faina Khoroshevsky, Boaz Lerner

Department of Industrial Engineering and Management

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

16 Scopus citations

Abstract

We provide a novel algorithm for the discovery of mobility patterns and prediction of users’ destination locations, both in terms of geographic coordinates and semantic meaning. We did not use any semantic data voluntarily provided by a user, and there was no sharing of data among the users. An advantage of our algorithm is that it allows a trade-off between prediction accuracy and information. Experimental validation was conducted on a GPS dataset collected in the Microsoft Research Asia GeoLife project by 168 users in a period of over five years.

Original language	English
Title of host publication	Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction - 4th IAPR TC 9 Workshop, MPRSS 2016, Revised Selected Papers
Editors	Stefan Scherer, Friedhelm Schwenker
Publisher	Springer Verlag
Pages	24-35
Number of pages	12
ISBN (Print)	9783319592589
DOIs	https://doi.org/10.1007/978-3-319-59259-6_3
State	Published - 1 Jan 2017
Event	4th IAPR TC 9 Workshop on Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2016 - Cancun, Mexico Duration: 4 Dec 2016 → 4 Dec 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10183 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th IAPR TC 9 Workshop on Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2016
Country/Territory	Mexico
City	Cancun
Period	4/12/16 → 4/12/16

Keywords

GeoLife
Human behavior
Location extraction
Mobility pattern
Next place prediction
Positioning technology
Semantic information
Stay point
Trajectory data

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-59259-6_3

Cite this

Khoroshevsky, F., & Lerner, B. (2017). Human mobility-pattern discovery and next-place prediction from GPS data. In S. Scherer, & F. Schwenker (Eds.), Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction - 4th IAPR TC 9 Workshop, MPRSS 2016, Revised Selected Papers (pp. 24-35). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10183 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-59259-6_3

Khoroshevsky, Faina ; Lerner, Boaz. / Human mobility-pattern discovery and next-place prediction from GPS data. Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction - 4th IAPR TC 9 Workshop, MPRSS 2016, Revised Selected Papers. editor / Stefan Scherer ; Friedhelm Schwenker. Springer Verlag, 2017. pp. 24-35 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{ea493545aa274679967a0d272474a7f5,

title = "Human mobility-pattern discovery and next-place prediction from GPS data",

abstract = "We provide a novel algorithm for the discovery of mobility patterns and prediction of users{\textquoteright} destination locations, both in terms of geographic coordinates and semantic meaning. We did not use any semantic data voluntarily provided by a user, and there was no sharing of data among the users. An advantage of our algorithm is that it allows a trade-off between prediction accuracy and information. Experimental validation was conducted on a GPS dataset collected in the Microsoft Research Asia GeoLife project by 168 users in a period of over five years.",

keywords = "GeoLife, Human behavior, Location extraction, Mobility pattern, Next place prediction, Positioning technology, Semantic information, Stay point, Trajectory data",

author = "Faina Khoroshevsky and Boaz Lerner",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 4th IAPR TC 9 Workshop on Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2016 ; Conference date: 04-12-2016 Through 04-12-2016",

year = "2017",

month = jan,

day = "1",

doi = "10.1007/978-3-319-59259-6_3",

language = "English",

isbn = "9783319592589",

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

publisher = "Springer Verlag",

pages = "24--35",

editor = "Stefan Scherer and Friedhelm Schwenker",

booktitle = "Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction - 4th IAPR TC 9 Workshop, MPRSS 2016, Revised Selected Papers",

address = "Germany",

}

Khoroshevsky, F & Lerner, B 2017, Human mobility-pattern discovery and next-place prediction from GPS data. in S Scherer & F Schwenker (eds), Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction - 4th IAPR TC 9 Workshop, MPRSS 2016, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10183 LNAI, Springer Verlag, pp. 24-35, 4th IAPR TC 9 Workshop on Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2016, Cancun, Mexico, 4/12/16. https://doi.org/10.1007/978-3-319-59259-6_3

Human mobility-pattern discovery and next-place prediction from GPS data. / Khoroshevsky, Faina; Lerner, Boaz.
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction - 4th IAPR TC 9 Workshop, MPRSS 2016, Revised Selected Papers. ed. / Stefan Scherer; Friedhelm Schwenker. Springer Verlag, 2017. p. 24-35 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10183 LNAI).

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

TY - GEN

T1 - Human mobility-pattern discovery and next-place prediction from GPS data

AU - Khoroshevsky, Faina

AU - Lerner, Boaz

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017/1/1

Y1 - 2017/1/1

N2 - We provide a novel algorithm for the discovery of mobility patterns and prediction of users’ destination locations, both in terms of geographic coordinates and semantic meaning. We did not use any semantic data voluntarily provided by a user, and there was no sharing of data among the users. An advantage of our algorithm is that it allows a trade-off between prediction accuracy and information. Experimental validation was conducted on a GPS dataset collected in the Microsoft Research Asia GeoLife project by 168 users in a period of over five years.

AB - We provide a novel algorithm for the discovery of mobility patterns and prediction of users’ destination locations, both in terms of geographic coordinates and semantic meaning. We did not use any semantic data voluntarily provided by a user, and there was no sharing of data among the users. An advantage of our algorithm is that it allows a trade-off between prediction accuracy and information. Experimental validation was conducted on a GPS dataset collected in the Microsoft Research Asia GeoLife project by 168 users in a period of over five years.

KW - GeoLife

KW - Human behavior

KW - Location extraction

KW - Mobility pattern

KW - Next place prediction

KW - Positioning technology

KW - Semantic information

KW - Stay point

KW - Trajectory data

UR - http://www.scopus.com/inward/record.url?scp=85021191967&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-59259-6_3

DO - 10.1007/978-3-319-59259-6_3

M3 - Conference contribution

AN - SCOPUS:85021191967

SN - 9783319592589

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

SP - 24

EP - 35

BT - Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction - 4th IAPR TC 9 Workshop, MPRSS 2016, Revised Selected Papers

A2 - Scherer, Stefan

A2 - Schwenker, Friedhelm

PB - Springer Verlag

T2 - 4th IAPR TC 9 Workshop on Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2016

Y2 - 4 December 2016 through 4 December 2016

ER -

Khoroshevsky F, Lerner B. Human mobility-pattern discovery and next-place prediction from GPS data. In Scherer S, Schwenker F, editors, Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction - 4th IAPR TC 9 Workshop, MPRSS 2016, Revised Selected Papers. Springer Verlag. 2017. p. 24-35. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-59259-6_3

Human mobility-pattern discovery and next-place prediction from GPS data

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this