research-article

Personalized Visited-POI Assignment to Individual Raw GPS Trajectories

Authors:

Yoshihiko Suhara,

Kyosuke NishidaAuthors Info & Claims

ACM Transactions on Spatial Algorithms and Systems (TSAS), Volume 5, Issue 3

Article No.: 16, Pages 1 - 28

https://doi.org/10.1145/3317667

Published: 12 August 2019 Publication History

Abstract

Knowledge discovery from GPS trajectory data is an essential topic in several scientific areas, including data mining, human behavior analysis, and user modeling. This article proposes a task that assigns personalized visited points of interest (POIs). Its goal is to assign every fine-grain location (i.e., POIs) that a user actually visited, which we call visited-POI, to the corresponding span of his or her (personal) GPS trajectories. We also introduce a novel algorithm to solve this assignment task. First, we exhaustively extract stay-points as span candidates of visits using a variant of a conventional stay-point extraction method and then extract POIs that are located close to the extracted stay-points as visited-POI candidates. Then, we simultaneously predict which stay-points and POIs can be actual user visits by considering various aspects, which we formulate as integer linear programming. Experimental results conducted on a real user dataset show that our method achieves higher accuracy in the visited-POI assignment task than the various cascaded procedures of conventional methods.

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Cited By

Löwens CThyssens DAndersson EJenkins CSchmidt-Thieme L(2023)DeepStay: Stay Region Extraction from Location Trajectories Using Weak Supervision2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)10.1109/ITSC57777.2023.10422584(3742-3748)Online publication date: 24-Sep-2023
https://doi.org/10.1109/ITSC57777.2023.10422584
Liu YDong B(2023)Modeling urban scale human mobility through big data analysis and machine learningBuilding Simulation10.1007/s12273-023-1043-z17:1(3-21)Online publication date: 14-Aug-2023
https://doi.org/10.1007/s12273-023-1043-z
Sasaki IArikawa MSato RTakahashi A(2022)Tourists Preferred Streets Visualization Using Articulated GPS Trajectories Driven by Mobile SensorsWeb and Wireless Geographical Information Systems10.1007/978-3-031-06245-2_4(43-50)Online publication date: 28-Apr-2022
https://dl.acm.org/doi/10.1007/978-3-031-06245-2_4
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Index Terms

Personalized Visited-POI Assignment to Individual Raw GPS Trajectories
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing theory, concepts and paradigms
      1. Ubiquitous computing
2. Information systems
  1. Information systems applications
    1. Data mining
    2. Spatial-temporal systems

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Published In

cover image ACM Transactions on Spatial Algorithms and Systems

ACM Transactions on Spatial Algorithms and Systems Volume 5, Issue 3

September 2019

189 pages

ISSN:2374-0353

EISSN:2374-0361

DOI:10.1145/3356873

Editor:
Walid G. Aref
Purdue University, USA

Issue’s Table of Contents

Copyright © 2019 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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Association for Computing Machinery

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Publication History

Published: 12 August 2019

Accepted: 01 February 2019

Revised: 01 January 2019

Received: 01 April 2017

Published in TSAS Volume 5, Issue 3

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Cited By

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https://doi.org/10.1109/ITSC57777.2023.10422584
Liu YDong B(2023)Modeling urban scale human mobility through big data analysis and machine learningBuilding Simulation10.1007/s12273-023-1043-z17:1(3-21)Online publication date: 14-Aug-2023
https://doi.org/10.1007/s12273-023-1043-z
Sasaki IArikawa MSato RTakahashi A(2022)Tourists Preferred Streets Visualization Using Articulated GPS Trajectories Driven by Mobile SensorsWeb and Wireless Geographical Information Systems10.1007/978-3-031-06245-2_4(43-50)Online publication date: 28-Apr-2022
https://dl.acm.org/doi/10.1007/978-3-031-06245-2_4
Sydorova MBaybuz OVerba OPidhornyi P(2021)INFORMATION TECHNOLOGY FOR TRAJECTORY DATA MININGScience and Innovation10.15407/scine17.03.07817:3(78-86)Online publication date: 17-Jun-2021
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Jeong SJeong DLee S(2021)Method of User Route Analysis based on POI through Stay Point IdentificationThe Journal of Korean Institute of Information Technology10.14801/jkiit.2021.19.11.119:11(1-12)Online publication date: 30-Nov-2021
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Lim JYoo SChung SKim GNoh KLim JJeong H(2021)SPER: Stay-Point Extraction considering Revisits in a Single Trajectory2021 International Conference on Information and Communication Technology Convergence (ICTC)10.1109/ICTC52510.2021.9621139(1555-1557)Online publication date: 20-Oct-2021
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