research-article

Link prediction in human mobility networks

Authors:

Nitesh V. Chawla,

Prithwish Basu,

Bhaskar Prabhala,

Thomas La PortaAuthors Info & Claims

ASONAM '13: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

Pages 380 - 387

https://doi.org/10.1145/2492517.2492656

Published: 25 August 2013 Publication History

Abstract

The understanding of how humans move is a longstanding challenge in the natural science. An important question is, to what degree is human behavior predictable? The ability to foresee the mobility of humans is crucial from predicting the spread of human to urban planning. Previous research has focused on predicting individual mobility behavior, such as the next location prediction problem. In this paper we study the human mobility behaviors from the perspective of network science. In the human mobility network, there will be a link between two humans if they are physically proximal to each other. We perform both microscopic and macroscopic explorations on the human mobility patterns. From the microscopic perspective, our objective is to answer whether two humans will be in proximity of each other or not. While from the macroscopic perspective, we are interested in whether we can infer the future topology of the human mobility network. In this paper we explore both problems by using link prediction technology, our methodology is demonstrated to have a greater degree of precision in predicting future mobility topology.

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Cited By

Wang CDeng Z(2023)Multi-perspective Spatiotemporal Context-aware Neural Networks for Human Mobility PredictionProceedings of the 1st International Workshop on the Human Mobility Prediction Challenge10.1145/3615894.3628502(32-36)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3615894.3628502
Stich CTranos EMusolesi MLehmann S(2021)The role of space, time and sociability in predicting social encountersEnvironment and Planning B: Urban Analytics and City Science10.1177/2399808321101687149:2(619-636)Online publication date: 4-Jun-2021
https://doi.org/10.1177/23998083211016871
Waqas MNiu YLi YAhmed MJin DChen SHan Z(2020)A Comprehensive Survey on Mobility-Aware D2D Communications: Principles, Practice and ChallengesIEEE Communications Surveys & Tutorials10.1109/COMST.2019.292370822:3(1863-1886)Online publication date: Nov-2021
https://doi.org/10.1109/COMST.2019.2923708
Show More Cited By

Index Terms

Link prediction in human mobility networks
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Web-based interaction
2. Information systems
  1. Information retrieval
    1. Document representation
  2. Information systems applications
    1. Data mining

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cover image ACM Conferences

ASONAM '13: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

August 2013

1558 pages

ISBN:9781450322409

DOI:10.1145/2492517

General Chairs:
Jon Rokne
University of Calgary, Calgary, AB, Canada
,
Christos Faloutsos
Carnegie Mellon University, Pittsburgh, PA

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 25 August 2013

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ASONAM '13: Advances in Social Networks Analysis and Mining 2013

August 25 - 28, 2013

Ontario, Niagara, Canada

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Overall Acceptance Rate 116 of 549 submissions, 21%

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Cited By

Wang CDeng Z(2023)Multi-perspective Spatiotemporal Context-aware Neural Networks for Human Mobility PredictionProceedings of the 1st International Workshop on the Human Mobility Prediction Challenge10.1145/3615894.3628502(32-36)Online publication date: 13-Nov-2023
https://dl.acm.org/doi/10.1145/3615894.3628502
Stich CTranos EMusolesi MLehmann S(2021)The role of space, time and sociability in predicting social encountersEnvironment and Planning B: Urban Analytics and City Science10.1177/2399808321101687149:2(619-636)Online publication date: 4-Jun-2021
https://doi.org/10.1177/23998083211016871
Waqas MNiu YLi YAhmed MJin DChen SHan Z(2020)A Comprehensive Survey on Mobility-Aware D2D Communications: Principles, Practice and ChallengesIEEE Communications Surveys & Tutorials10.1109/COMST.2019.292370822:3(1863-1886)Online publication date: Nov-2021
https://doi.org/10.1109/COMST.2019.2923708
Gade SAhmed MDeb SGanguly A(2019)Energy Efficient Chip-to-Chip Wireless Interconnection for Heterogeneous ArchitecturesACM Transactions on Design Automation of Electronic Systems10.1145/334010924:5(1-27)Online publication date: 26-Jul-2019
https://dl.acm.org/doi/10.1145/3340109
Wang JKong XXia FSun L(2019)Urban Human MobilityACM SIGKDD Explorations Newsletter10.1145/3331651.333165321:1(1-19)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3331651.3331653
Li TSapatnekar S(2019)Stress-Induced Performance Shifts in 3D DRAMsACM Transactions on Design Automation of Electronic Systems10.1145/333152724:5(1-21)Online publication date: 26-Jun-2019
https://dl.acm.org/doi/10.1145/3331527
Wang HHe K(2019)Improving Test and Diagnosis Efficiency through Ensemble Reduction and LearningACM Transactions on Design Automation of Electronic Systems10.1145/332875424:5(1-26)Online publication date: 5-Jun-2019
https://dl.acm.org/doi/10.1145/3328754
Fan SZahedi SLee B(2019)Distributed strategies for computational sprintsCommunications of the ACM10.1145/329988562:2(98-106)Online publication date: 28-Jan-2019
https://dl.acm.org/doi/10.1145/3299885
Feitelson D(2019)Tony's lawCommunications of the ACM10.1145/329980062:2(28-31)Online publication date: 28-Jan-2019
https://dl.acm.org/doi/10.1145/3299800
Hsieh HLi C(2019)Inferring Online Social Ties from Offline Geographical ActivitiesACM Transactions on Intelligent Systems and Technology10.1145/329331910:2(1-21)Online publication date: 12-Jan-2019
https://dl.acm.org/doi/10.1145/3293319
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