- This repository is for paper High Precision
$\neq$ High Cost: Temporal Data Fusion for Multiple Low-Precision Sensors.
- code: source code of algorithms.
- The functions have the same names as the algorithms in the paper.
- As for TruthFinder, Sums, Investment, CRH, GATD, we use the open source implemenations for them, i.e.,
- TruthFinder, Sums, Investment: https://github.com/joesingo/truthdiscovery
- CRH, GATD: https://sites.google.com/iastate.edu/qili
- data: dataset source files used in experiments.
- full.pdf: the full version of our manuscript, including all the complete proofs in appendix.
- GPS
- Manual collection
- Format: timestamp(1),observations from different sensors(2-5), true value(6)
- WEATHER
- https://www.aerisweather.com
- https://www.worldweatheronline.com/
- https://www.wunderground.com/
- run gen_weather.py with the ID get from the official website and parameters specified in the code.
- IMU: https://github.com/dusan-nemec/mems-calib
- GINS: https://github.com/i2Nav-WHU/awesome-gins-datasets
numpy==1.24.2
pandas==1.4.3
pyclustering==0.10.1.2
scikit_learn==1.1.1
To run the program, use the following command-line arguments:
--dataname
: Input file name (default is "GPS").--alg
: Method name (default is "DFDP").--k
: The parameter kappa (default is 3).
eg.
main.py --data GPS --alg DFRC --k 3
or you can run directly:
cd code
python main.py