research-article

G-RoI: Automatic Region-of-Interest Detection Driven by Geotagged Social Media Data

Authors:

Loris Belcastro,

Fabrizio Marozzo,

Domenico Talia,

Paolo TrunfioAuthors Info & Claims

ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 12, Issue 3

Article No.: 27, Pages 1 - 22

https://doi.org/10.1145/3154411

Published: 23 January 2018 Publication History

Abstract

Geotagged data gathered from social media can be used to discover interesting locations visited by users called Places-of-Interest (PoIs). Since a PoI is generally identified by the geographical coordinates of a single point, it is hard to match it with user trajectories. Therefore, it is useful to define an area, called Region-of-Interest (RoI), to represent the boundaries of the PoI’s area. RoI mining techniques are aimed at discovering ROIs from PoIs and other data. Existing RoI mining techniques are based on three main approaches: predefined shapes, density-based clustering, and grid-based aggregation. This article proposes G-RoI, a novel RoI mining technique that exploits the indications contained in geotagged social media items to discover RoIs with a high accuracy. Experiments performed over a set of PoIs in Rome and Paris using social media geotagged data, demonstrate that G-RoI in most cases achieves better results than existing techniques. In particular, the mean F₁ score is 0.34 higher than that obtained with the well-known DBSCAN algorithm in Rome RoIs and 0.23 higher in Paris RoIs.

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Cited By

Bin Asad KYuan Y(2024)The Impact of Scale on Extracting Individual Mobility Patterns from Location-Based Social MediaSensors10.3390/s2412379624:12(3796)Online publication date: 12-Jun-2024
https://doi.org/10.3390/s24123796
Fazal NFränti P(2024)Social media data for content creation in location-based gamesJournal of Location Based Services10.1080/17489725.2024.2414000(1-28)Online publication date: 30-Oct-2024
https://doi.org/10.1080/17489725.2024.2414000
Marozzo FTalia D(2023)Perspectives on Big Data, Cloud-Based Data Analysis and Machine Learning SystemsBig Data and Cognitive Computing10.3390/bdcc70201047:2(104)Online publication date: 30-May-2023
https://doi.org/10.3390/bdcc7020104
Show More Cited By

Index Terms

G-RoI: Automatic Region-of-Interest Detection Driven by Geotagged Social Media Data
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing design and evaluation methods
      1. Social network analysis
2. Information systems
  1. Information retrieval
    1. Specialized information retrieval
      1. Environment-specific retrieval
        Web and social media search
  2. Information systems applications
    1. Collaborative and social computing systems and tools

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Published In

cover image ACM Transactions on Knowledge Discovery from Data

ACM Transactions on Knowledge Discovery from Data Volume 12, Issue 3

June 2018

360 pages

ISSN:1556-4681

EISSN:1556-472X

DOI:10.1145/3178546

Editors:
Charu Aggarwal
IBM T. J. Watson Research, USA
,
Xindong Wu
University of Louisiana at Lafayette, USA

Issue’s Table of Contents

Copyright © 2018 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 January 2018

Accepted: 01 October 2017

Revised: 01 September 2017

Received: 01 July 2016

Published in TKDD Volume 12, Issue 3

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Cited By

Bin Asad KYuan Y(2024)The Impact of Scale on Extracting Individual Mobility Patterns from Location-Based Social MediaSensors10.3390/s2412379624:12(3796)Online publication date: 12-Jun-2024
https://doi.org/10.3390/s24123796
Fazal NFränti P(2024)Social media data for content creation in location-based gamesJournal of Location Based Services10.1080/17489725.2024.2414000(1-28)Online publication date: 30-Oct-2024
https://doi.org/10.1080/17489725.2024.2414000
Marozzo FTalia D(2023)Perspectives on Big Data, Cloud-Based Data Analysis and Machine Learning SystemsBig Data and Cognitive Computing10.3390/bdcc70201047:2(104)Online publication date: 30-May-2023
https://doi.org/10.3390/bdcc7020104
Zhu YChen LXiong DChen SDu FHao JHe RSun ZSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)C-AOI: Contour-based Instance Segmentation for High-Quality Areas-of-Interest in Online Food Delivery PlatformProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599786(5750-5759)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599786
Marozzo FBelcastro L(2022)Cloud Computing for Big Data AnalysisApplied Sciences10.3390/app12201056712:20(10567)Online publication date: 19-Oct-2022
https://doi.org/10.3390/app122010567
Belcastro LCantini RMarozzo F(2022)Knowledge Discovery from Large Amounts of Social Media DataApplied Sciences10.3390/app1203120912:3(1209)Online publication date: 24-Jan-2022
https://doi.org/10.3390/app12031209
Belcastro LCantini RMarozzo FOrsino ATalia DTrunfio P(2022)Programming big data analysis: principles and solutionsJournal of Big Data10.1186/s40537-021-00555-29:1Online publication date: 6-Jan-2022
https://doi.org/10.1186/s40537-021-00555-2
Chen LXiong DChen SDu FHe RSun ZRenz MSarwat M(2022)Automatic generation of areas of interest using multimodal geospatial data from an on-demand food delivery platform (industrial paper)Proceedings of the 30th International Conference on Advances in Geographic Information Systems10.1145/3557915.3561023(1-10)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1145/3557915.3561023
Li BChen LXiong DChen SHe RSun ZLim SJiang HRenz MSarwat M(2022)Simultaneous detection of multiple areas-of-interest using geospatial data from an online food delivery platform (industrial paper)Proceedings of the 30th International Conference on Advances in Geographic Information Systems10.1145/3557915.3561014(1-10)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1145/3557915.3561014
Li BGao JChen SLim SJiang H(2022)POI Detection of High-Rise Buildings Using Remote Sensing Images: A Semantic Segmentation Method Based on Multitask Attention Res-U-NetIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2022.317439960(1-16)Online publication date: 2022
https://doi.org/10.1109/TGRS.2022.3174399
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