Worker Collaborative group estimation in spatial crowdsourcing-Reference-Cited by-同舟云学术

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Worker Collaborative group estimation in spatial crowdsourcing

Published:2021-03 Issue: Volume:428 Page:385-391
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Wang Zhi,Li Yubing,Zhao Kun,Shi Wei,Lin Liangliang,Zhao Jizhong

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference41 articles.

1. Gigwalk (http://www.gigwalk.com).

2. Gmission (http://gmissionhkust.com).

3. Openstreetmap (https://www.openstreetmap.org).

4. Top-k team recommendation and its variants in spatial crowdsourcing;Gao;Data Sci. Eng.,2017

5. Collective travel planning in spatial networks;Shang;IEEE Trans. Knowl. Data Eng.,2016

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2. Optimizing Collaborative Crowdsensing: A Graph Theoretical Approach to Team Recruitment and Fair Incentive Distribution;Sensors;2024-05-08

3. Coalition-based task assignment with priority-aware fairness in spatial crowdsourcing;The VLDB Journal;2023-07-07

4. Efficient Cross Dynamic Task Assignment in Spatial Crowdsourcing;2023 IEEE 39th International Conference on Data Engineering (ICDE);2023-04

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