TaskMe

Author:

Liu Yan1,Guo Bin1,Wang Yang2,Wu Wenle1,Yu Zhiwen1,Zhang Daqing3

Affiliation:

1. Northwestern Polytechnical University, Xi'an 710129, Shaanxi, China

2. Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China

3. Institut Mines-Télécom, Télécom SudParis, CNRS SAMOVAR, Evry 91011, France

Funder

National Basic Research Program of China

Publisher

ACM

Reference33 articles.

1. Selecting skyline services for QoS-based web service composition

2. V.D. Blondel M. Esch C. Chan F. Clerot P. Deville E. Huens F. Morlot Z. Smoreda and C. Ziemlicki. 2012. Data for development: the d4d challenge on mobile phone data. arXiv preprint arXiv:1210.0137. V.D. Blondel M. Esch C. Chan F. Clerot P. Deville E. Huens F. Morlot Z. Smoreda and C. Ziemlicki. 2012. Data for development: the d4d challenge on mobile phone data. arXiv preprint arXiv:1210.0137.

3. Amazon's Mechanical Turk

4. Campaignr: http://research.cens.ucla.edu/urban/ Campaignr: http://research.cens.ucla.edu/urban/

5. Fostering participaction in smart cities: a geo-social crowdsensing platform

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1. LSTM-Oppurs: Opportunistic user recruitment strategy based on deep learning in mobile crowdsensing system;Future Generation Computer Systems;2025-01

2. Task Assignment in Extreme Edge Sensing: Balancing Response Time and Incentives;ICC 2024 - IEEE International Conference on Communications;2024-06-09

3. Paintings, Not Noise—The Role of Presentation Sequence in Labeling;Interacting with Computers;2024-03-15

4. Snap’N’Go: An Extendable Framework for Evaluating Mechanisms in Mobile Crowdsensing;2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops);2024-03-11

5. Challenges of Modeling Participant Behavior in CrowdSensing Evaluation;2024 IEEE 21st Consumer Communications & Networking Conference (CCNC);2024-01-06

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