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Exploring the use of Bayesian probabilistic techniques and Graphical Neural Networks to detect plagiarism!

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kenghweeng/bayesian_beats_cheats

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CS5340: Group 10 - Bayesian Beats Cheats

Once you go Bayesian, there is no evasion!

Commit guidelines:

Organised our project into the following folder structure:

  • Iterative_Classification [Jihui and YingYing]
  • Loopy_BP [Zihan]
  • GNN [Keng Hwee]
  • app [Initial Streamlit prototyping for future considerations]
  • data [data after node pre-processing done by Jonathan and edge pre-processing done by Leonard]
  • raw_data [data collected from Coursemology and MOSS outputs done by Jonathan]
  • src [preprocessing code provided by team]
  • runs [Tensorboard logs from Keng Hwee's GNN training, run tensorboard --logdir runs to see them!]
  • random_walk [Baseline experiment from Jonathan to find influential nodes]
  • requirements.txt [Python modules for reproducibility]

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Exploring the use of Bayesian probabilistic techniques and Graphical Neural Networks to detect plagiarism!

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