This repository contains scripts for running (dynamic) Bernoulli embeddings on text data. They have been run and tested on Linux.
To execute, go into the source folder (src/) and run
python main.py --dynamic True --fpath [path/to/data]
substitute the path to the folder where you put the data for [path/to/data].
The data folder and files have to be structured in a specific format.
For your convenience, we included some scripts that will help you preprocess the text data in dat/src/. For instructions on the required data format see dat/README.md.
For all commandline options run:
python main.py --help
For fastest convergence we recommend the following 2-step training procedure. First run
python main.py --fpath [path/to/data]
This executes Bernoulli embeddings without dynamics. The scripts uses the current timestamp to create a folder where the results are saved ([path/to/results/]). We will use these results to initialize the dynamic embeddings:
python main.py --dynamic True --fpath [path/to/data] --init [path/to/result]/alpha_constant
Make sure to use the same --K for both runs.
Maja Rudolph and David Blei, 2017. Dynamic Bernoulli Embeddings for Language Evolution. arxiv preprint arxiv:1703.08052.