This code requires Python 3.6 or higher, and relies on the following packages:
- gensim
- matplotlib
- numpy
- scipy
To create a model, run:
python main.py [epochs] [vector_size] [window]
This will generate a model using Doc2Vec and create a histogram to visualize the model performance. The model will be saved to models/epochs_[epochs]_vectorSize_[vector_size]_window_[window].model and the histogram will be saved to histograms/epochs_[epochs]_vectorSize_[vector_size]_window_[window].png.
The name pairings used to create histograms are randomly generated the first time they are required, at which point they are saved to cache/index_pairs.json. These saved name pairings will be reused when generating histograms for additional models.
The distance of each name pair used to create a histogram is also saved. These values can be found in the matching_name_distance and random_name_distance directories.
The data that allowed for this experimentation was made availible by: