Docker allows an easy execution of the provided scripts by creating a container that installs all the needed dependencies. This folder contains a Dockerfile that installs a Python 3.6 environment. The environment can be used to run and evaluate the provided PubMed abstract clustering algorithm.

First, install Docker as described in the documentation: https://docs.docker.com/engine/installation/

Then, build, from the root folder of the repository, the docker container. Run:

docker build ./docker/ -t pubmed_clustering

This builds the Python 3.6 container and assigns the name pubmed_clustering to it.

To run the code, we must first start the container and mount the current folder $PWD into the container:

docker run -it -v "$PWD":/src pubmed_clustering bash

The command -v "$PWD":/src maps the current folder $PWD into the docker container at the position /src. Changes made on the host system as well as in the container are synchronized. We can change / add / delete files in the current folder and its subfolder and can access those files directly in the docker container.

Windows users can use the command %cd% instead of $PWD to get a path to current folder.

In this container, you can run execute the scripts as usual. For example, to cluster the abstracts, run:

python cluster_abstracts.py pmids_gold_set_unlabeled.txt