research-article

GeoCrowd: enabling query answering with spatial crowdsourcing

Authors:

Cyrus ShahabiAuthors Info & Claims

SIGSPATIAL '12: Proceedings of the 20th International Conference on Advances in Geographic Information Systems

Pages 189 - 198

https://doi.org/10.1145/2424321.2424346

Published: 06 November 2012 Publication History

Abstract

With the ubiquity of mobile devices, spatial crowdsourcing is emerging as a new platform, enabling spatial tasks (i.e., tasks related to a location) assigned to and performed by human workers. In this paper, for the first time we introduce a taxonomy for spatial crowdsourcing. Subsequently, we focus on one class of this taxonomy, in which workers send their locations to a centralized server and thereafter the server assigns to every worker his nearby tasks with the objective of maximizing the overall number of assigned tasks. We formally define this maximum task assignment (or MTA) problem in spatial crowdsourcing, and identify its challenges. We propose alternative solutions to address these challenges by exploiting the spatial properties of the problem space. Finally, our experimental evaluations on both real-world and synthetic data verify the applicability of our proposed approaches and compare them by measuring both the number of assigned tasks and the travel cost of the workers.

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Cited By

Aburas HShahrour ISadek M(2024)Leveraging Crowdsourcing for Mapping Mobility Restrictions in Data-Limited RegionsSmart Cities10.3390/smartcities70501007:5(2572-2593)Online publication date: 7-Sep-2024
https://doi.org/10.3390/smartcities7050100
Li MWang WZhang J(2024)Towards Efficient and Deposit-Free Blockchain-Based Spatial CrowdsourcingACM Transactions on Sensor Networks10.1145/365634320:3(1-22)Online publication date: 9-Apr-2024
https://dl.acm.org/doi/10.1145/3656343
Lin FTsai PLee CHo YChen YYen YChang Y(2024)“I Prefer Regular Visitors to Answer My Questions”: Users’ Desired Experiential Background of Contributors for Location-based Crowdsourcing PlatformProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642520(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642520
Show More Cited By

Index Terms

GeoCrowd: enabling query answering with spatial crowdsourcing
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Geographic visualization
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems

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Published In

cover image ACM Conferences

SIGSPATIAL '12: Proceedings of the 20th International Conference on Advances in Geographic Information Systems

November 2012

642 pages

ISBN:9781450316910

DOI:10.1145/2424321

General Chairs:
Isabel Cruz
University of Illinois at Chicago
,
Craig Knoblock
University of Southern California
,
Program Chairs:
Peer Kröger
Ludwig-Maximilians-Universität München, Germany
,
Egemen Tanin
University of Melbourne, Australia
,
Peter Widmayer
ETH Zürich, Switzerland

Copyright © 2012 ACM.

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

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Published: 06 November 2012

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SIGSPATIAL'12: SIGSPATIAL 2012 International Conference on Advances in Geographic Information Systems

November 6 - 9, 2012

Redondo Beach, California

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Cited By

Aburas HShahrour ISadek M(2024)Leveraging Crowdsourcing for Mapping Mobility Restrictions in Data-Limited RegionsSmart Cities10.3390/smartcities70501007:5(2572-2593)Online publication date: 7-Sep-2024
https://doi.org/10.3390/smartcities7050100
Li MWang WZhang J(2024)Towards Efficient and Deposit-Free Blockchain-Based Spatial CrowdsourcingACM Transactions on Sensor Networks10.1145/365634320:3(1-22)Online publication date: 9-Apr-2024
https://dl.acm.org/doi/10.1145/3656343
Lin FTsai PLee CHo YChen YYen YChang Y(2024)“I Prefer Regular Visitors to Answer My Questions”: Users’ Desired Experiential Background of Contributors for Location-based Crowdsourcing PlatformProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642520(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642520
Ma YGao XBhatti SChen G(2024)Clustering Based Priority Queue Algorithm for Spatial Task Assignment in CrowdsourcingIEEE Transactions on Services Computing10.1109/TSC.2024.335329317:2(452-465)Online publication date: Mar-2024
https://doi.org/10.1109/TSC.2024.3353293
Wu QLi YZhu GMei BXu JXu M(2024)Prediction-Aware Adaptive Task Assignment for Spatial CrowdsourcingIEEE Transactions on Mobile Computing10.1109/TMC.2024.342339623:12(13048-13061)Online publication date: Dec-2024
https://doi.org/10.1109/TMC.2024.3423396
Yu ZZhao LCui HSong YLiu YLuo YGuo B(2024)CrowdKit: A Generic Programming Framework for Mobile Crowdsensing ApplicationsIEEE Transactions on Mobile Computing10.1109/TMC.2024.338157823:11(10584-10597)Online publication date: Nov-2024
https://doi.org/10.1109/TMC.2024.3381578
Ni WCheng PChen LYang S(2024)Task Assignment Framework for Online Car-Hailing Systems With Electric VehiclesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.343456736:12(9361-9373)Online publication date: Dec-2024
https://doi.org/10.1109/TKDE.2024.3434567
Zhao YChen XYe GGuo FZheng KZhou X(2024)Task Allocation in Spatial Crowdsourcing: An Efficient Geographic Partition FrameworkIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.337408636:9(4943-4955)Online publication date: Sep-2024
https://doi.org/10.1109/TKDE.2024.3374086
Xie WChen ZZhang CZheng LCheng PYin JLin X(2024)Longer Pick-Up for Less Pay: Towards Discount-Based Mobility ServicesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.336289336:8(3992-4006)Online publication date: Aug-2024
https://doi.org/10.1109/TKDE.2024.3362893
Xie YWu FZhou XLuo WYin YZimmermann RLi KLi K(2024)Trajectory-Aware Task Coalition Assignment in Spatial CrowdsourcingIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.333664236:11(7201-7216)Online publication date: Nov-2024
https://doi.org/10.1109/TKDE.2023.3336642
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