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BiGIT is a graph-based method capable of transferring information from and to different nodes on a bipartite graph. This project contains BiGIT combined with several work representation methods since it was created for experimentation purposes.
Classification of acronyms and their long forms using an RNN (LSTM), CNN, and FFNN model. The experiments focused on the RNN and used different vectorisation methods and hyperparameters. Models were built with Keras and the notebook code runs on Google Colab.