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Author Identification Project

Kahlil Khan / kkhan37 / CS-6460 Educational Technology / Summer 2018

Description of files

  • open.ipynb: Jupyter notebook. Trains the author identification model. Status: Complete.
  • origin.py: Python. The external tool. Provides interface to connect Canvas. Status: Draft interface works command line, not yet with Canvas (requires JSON formatting)
  • origin-test.ipynb: Jupyter notebook. Demonstration surogate for Canvas LMS.
  • lti.ipynb: Jupyter notebook. Alpha-level attempt to connect to Canvas via its LTI version 1 and 2 interfaces.
  • environment.yml: Text. Listing of development dependencies. See installation instructions below.

Description of data

  • data/C50/C50all/: 5051 articles from 50 authors. This is a combination of the training and test data from Reuter_50_50 dataset
  • data/5-300-lstm128-128-20-50-model.h5: The trained Keras model. Trained by open.ipynb and used in orgin.py.

Installation instructions

  1. Install and run mongo database: macos or linux.
  2. Install anaconda from https://www.anaconda.com
  3. conda env create -f environment.yml
  4. source activate tensorflow_p36
  5. jupyter lab
  6. Open origin-test.ipynb

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Contributors

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