research-article

Characterizing the life cycle of point of interests using human mobility patterns

Authors:

Chu GuanAuthors Info & Claims

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Pages 1052 - 1063

https://doi.org/10.1145/2971648.2971749

Published: 12 September 2016 Publication History

Abstract

A Point of Interest (POI) refers to a specific location that people may find useful or interesting. While a large body of research has been focused on identifying and recommending POIs, there are few studies on characterizing the life cycle of POIs. Indeed, a comprehensive understanding of POI life cycle can be helpful for various tasks, such as urban planning, business site selection, and real estate evaluation. In this paper, we develop a framework, named POLIP, for characterizing the POI life cycle with multiple data sources. Specifically, to investigate the POI evolution process over time, we first formulate a serial classification problem to predict the life status of POIs. The prediction approach is designed to integrate two important perspectives: 1) the spatial-temporal dependencies associated with the prosperity of POIs, and 2) the human mobility dynamics hidden in the citywide taxicab data related to the POIs at multiple granularity levels. In addition, based on the predicted life statuses in successive time windows for a given POI, we design an algorithm to characterize its life cycle. Finally, we performed extensive experiments using large-scale and real-world datasets. The results demonstrate the feasibility in automatic characterizing POI life cycle and shed important light on future research directions.

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Cited By

Liu HGuo QZhu HFu YZhuang FMa XXiong H(2023)Characterizing and Forecasting Urban Vibrancy Evolution: A Multi-View Graph Mining PerspectiveACM Transactions on Knowledge Discovery from Data10.1145/356868317:5(1-24)Online publication date: 28-Feb-2023
https://dl.acm.org/doi/10.1145/3568683
Chen HMa GHuang Y(2023)Spatiotemporal Task Allocation in Mobile CrowdsensingMobile Crowdsourcing10.1007/978-3-031-32397-3_7(163-189)Online publication date: 21-Apr-2023
https://doi.org/10.1007/978-3-031-32397-3_7
Huang JWang HFan MZhuo ASun YLi YGupta RLiu YShah MRajan STang JPrakash B(2020)Understanding the Impact of the COVID-19 Pandemic on Transportation-related Behaviors with Human Mobility DataProceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3394486.3412856(3443-3450)Online publication date: 23-Aug-2020
https://dl.acm.org/doi/10.1145/3394486.3412856
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Index Terms

Characterizing the life cycle of point of interests using human mobility patterns
1. Information systems
  1. Information systems applications

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Published In

cover image ACM Conferences

UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 2016

1288 pages

ISBN:9781450344616

DOI:10.1145/2971648

General Chairs:
Paul Lukowicz
DFKI and University of Kaiserslautern
,
Antonio Krüger
DFKI and Saarland University
,
Program Chairs:
Andreas Bulling
Max Planck Institute for Informatics
,
Youn-Kyung Lim
KAIST
,
Shwetak N. Patel
University of Washington

Copyright © 2016 ACM.

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Published: 12 September 2016

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National Natural Science Foundation of China
Microsoft
National Basic Research Program of China

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UbiComp '16

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UbiComp '16: The 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing

September 12 - 16, 2016

Germany, Heidelberg

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UbiComp '16 Paper Acceptance Rate 101 of 389 submissions, 26%;

Overall Acceptance Rate 764 of 2,912 submissions, 26%

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Cited By

Liu HGuo QZhu HFu YZhuang FMa XXiong H(2023)Characterizing and Forecasting Urban Vibrancy Evolution: A Multi-View Graph Mining PerspectiveACM Transactions on Knowledge Discovery from Data10.1145/356868317:5(1-24)Online publication date: 28-Feb-2023
https://dl.acm.org/doi/10.1145/3568683
Chen HMa GHuang Y(2023)Spatiotemporal Task Allocation in Mobile CrowdsensingMobile Crowdsourcing10.1007/978-3-031-32397-3_7(163-189)Online publication date: 21-Apr-2023
https://doi.org/10.1007/978-3-031-32397-3_7
Huang JWang HFan MZhuo ASun YLi YGupta RLiu YShah MRajan STang JPrakash B(2020)Understanding the Impact of the COVID-19 Pandemic on Transportation-related Behaviors with Human Mobility DataProceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining10.1145/3394486.3412856(3443-3450)Online publication date: 23-Aug-2020
https://dl.acm.org/doi/10.1145/3394486.3412856
Lu XYu ZLiu CLiu YXiong HGuo B(2020)Inferring Lifetime Status of Point-of-InterestACM Transactions on Knowledge Discovery from Data10.1145/336979914:1(1-27)Online publication date: 3-Feb-2020
https://dl.acm.org/doi/10.1145/3369799
Kwon YChatzopoulos Dul Haq EWong RHui P(2019)GeoLifecycleProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/33512503:3(1-29)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1145/3351250
Suzuki JSuhara YToda HNishida K(2019)Personalized Visited-POI Assignment to Individual Raw GPS TrajectoriesACM Transactions on Spatial Algorithms and Systems10.1145/33176675:3(1-28)Online publication date: 12-Aug-2019
https://dl.acm.org/doi/10.1145/3317667
Ouyang YGuo BLu XHan QGuo TYu Z(2019)CompetitiveBike: Competitive Analysis and Popularity Prediction of Bike-Sharing Apps Using Multi-Source DataIEEE Transactions on Mobile Computing10.1109/TMC.2018.286893318:8(1760-1773)Online publication date: 1-Aug-2019
https://doi.org/10.1109/TMC.2018.2868933
Ouyang YGuo BLu XHan QGuo TYu Z(2019)CompetitiveBike: Competitive Prediction of Bike-Sharing Apps Using Heterogeneous Crowdsourced DataGreen, Pervasive, and Cloud Computing10.1007/978-3-030-15093-8_17(241-255)Online publication date: 15-Mar-2019
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Cao HChen ZXu FLi YKostakos V(2018)Revisitation in Urban Space vs. OnlineProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/32870342:4(1-24)Online publication date: 27-Dec-2018
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Cao HFeng JLi YKostakos V(2018)Uniqueness in the CityProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/32142652:2(1-20)Online publication date: 5-Jul-2018
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