SpatialCrowdsourcing-MWATP: Multi-Worker-Aware Task Planning in Real-Time Spatial Crowdsourcing

This repository stores the source code of the proposed solutions to the problem called MWATP in the following paper.

[1] Multi-Worker-Aware Task Planning in Real-Time Spatial Crowdsourcing. Qian Tao, Yuxiang Zeng, Zimu Zhou, Yongxin Tong, Lei Chen, Ke Xu. DASFAA 2018: 301-317. link

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

@inproceedings{DBLP:conf/dasfaa/TaoZZTC018,
  author    = {Qian Tao and
               Yuxiang Zeng and
               Zimu Zhou and
               Yongxin Tong and
               Lei Chen and
               Ke Xu},
  title     = {Multi-Worker-Aware Task Planning in Real-Time Spatial Crowdsourcing},
  booktitle = {{DASFAA}},
  pages     = {301--317},
  year      = {2018},
}

Usage of the algorithms

Environment

gcc/g++ version: 7.4.0

OS: Ubuntu

Compile the algorithms

cd algorithm && make all

ignore: the Delay-Planning algorithm in the paper

replan: the Fast-Planning algorithm in the paper

Run the algorithms

./replan ../dataset/synthetic/0100_3000_0090_0180_06/data_00.txt

./ignore ../dataset/synthetic/0100_3000_0090_0180_06/data_00.txt

0100_3000_0090_0180_06: the varied paramters in the experiments

data_00.txt: the information of the tasks and workers (i.e., the input)

Description of the data generator

Environment

Python: 2.7

Run the scripts

genDataSynthetic.py: a script to generate the synthetic datasets in the experiments

synthetic: a sample of the synthetic datasets

Related resources

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

Contact

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