graphB

graphB algorithmm implements graph frustration cloud and resulting concensus measures

** Automated run on sample data** - The example is set to run 10 trees >>source [testRun.sh](testRun.sh] graphB notebook contains detailed setup and run steps

Citation

Please cite this publication: Rusnak, L., Tešić, J. Characterizing attitudinal network graphs through frustration cloud. Data Min Knowl Disc 35, 2498–2539 (2021).

BibTeX entry:

@article{2020Cloud,
  author       = {Lucas Rusnak and Jelena Te\v{s}i\'{c}},
  title        = {Characterizing Attitudinal Network Graphs through Frustration Cloud},
  journal = {Data Mining and Knowledge Discovery},
  volume = {6},
  no = {35},
  month        = {November},
  year         = {2021},
  publisher = {Springer},
  doi = {https://doi.org/10.1007/s10618-021-00795-z}
}

Docker image of the test run

1. Install Docker
2. In terminal:

>>docker pull jtesic/graph_balancing:latest
>>docker run latest

• To build docker image in current folder

>>docker build -t latest .
>>docker run latest
>>docker tag latest <USERNAME>/<REPO>:latest
>>docker push <USERNAME>/<REPO>:latest

Next Steps

• Timing Analysis experiment
• Detailed timing experiment
• Data Format and code run

Data Lab @ TXST