GOMA: Two-sided Online Micro-Task Assignment in Spatial Crowdsourcing

This repository stores the source code of the solutions to the problem called GOMA in the following papers. Our appendix (i.e., the full paper) has also been uploaded here (i.e., TKDE-goma-Appendix.pdf).

[1] Two-sided Online Micro-Task Assignment in Spatial Crowdsourcing. Yongxin Tong, Yuxiang Zeng, Bolin Ding, Libin Wang, Lei Chen. IEEE Transactions on Knowledge and Data Engineering, 2019. link

[2] Online mobile Micro-Task Allocation in spatial crowdsourcing. Yongxin Tong, Jieying She, Bolin Ding, Libin Wang, Lei Chen. ICDE 2016: 49-60. link slides

If you find our work helpful in your research, please consider citing our papers and the bibtex are listed below:

@article{tong2019two,  
  title={Two-sided Online Micro-Task Assignment in Spatial Crowdsourcing},  
  author={Tong, Yongxin and Zeng, Yuxiang and Ding, Boling and Wang, Libin and Chen, Lei},  
  journal={IEEE Transactions on Knowledge and Data Engineering},  
  year={2019},  
}  
@inproceedings{DBLP:conf/icde/TongSDWC16,
  author    = {Yongxin Tong and
               Jieying She and
               Bolin Ding and
               Libin Wang and
               Lei Chen},
  title     = {Online mobile Micro-Task Allocation in spatial crowdsourcing},
  booktitle = {{ICDE}},
  pages     = {49--60},
  year      = {2016},
}

Usage of the algorithms

Environment

gcc/g++ version: 7.4.0

OS: Ubuntu

Compile the algorithms

cd algorithm && make all

Run the algorithms

./TGOA-OP ./realData/EverySender_cap1/data_00.txt

./Greedy ./realData/EverySender_cap1/data_00.txt

./TGOA ./realData/EverySender_cap1/data_00.txt

./TGOA-Greedy ./realData/EverySender_cap1/data_00.txt

./Ext-GRT ./realData/EverySender_cap1/data_00.txt

./OPT ./realData/EverySender_cap1/data_00.txt

Description of the datasets

Environment

Python: 2.7

Synthetic dataset

dataset/synthetic: a sample of our synthetic dataset (#2)

dataset/genDataSynthetic.py: a script to generate the synthetic datasets

Please refer to genDataSynthetic.py for the format of the dataset.

Real dataset

dataset/real/EverySender*: includes the datasets of EverySende

dataset/real/gMission*: incldues the datasets of gMission

Please refer to the source code for the format of the dataset.

Related resources

We have maintained a paper list of the studies on spatial crowdsourcing. link

Contact

• Yuxiang Zeng: yzengal@cse.ust.hk
• Yongxin Tong: yxtong@buaa.edu.cn