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},
}

gcc/g++ version: 7.4.0

OS: Ubuntu

cd algorithm && make all

./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

Python: 2.7

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.

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.

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

• Yuxiang Zeng: [email protected]
• Yongxin Tong: [email protected]