Generates text summaries from given inputs through several methods. supports Korean only, for now.

Currently implemented methods:

• Pointer-Generator Network (most codes are from this project with some modification.)
• TextRank (by textrankr library)
• Transformer

This is a sub-project of skku-coop-project backed by SK Planet.

hanja
textrankr
django
tensorflow >= 2.0.0
koalanlp

NOTE: Now all requirements are included. No need to download.

• khaiii
• Stanford CoreNLP

• Automated bash script is included. Now you just need to run run_demo.sh only.
• I recommend to use python virtual environment venv to isolate the development environment.

Before running demo page server, you should export your working directory as PYTHONPATH. Try with this:

export PYTHONPATH=$PYTHONPATH:path/to/project

Also this project uses Stanford CoreNLP library to regularize input sentences. We assume you already installed Java runtime & downloaded CoreNLP library.

Like PYTHONPATH, to run the server you need to specify CoreNLP jar file into CLASSPATH. Try with this:

export CLASSPATH=$CLASSPATH:path/to/corenlp/stanford-corenlp-(version number).jar

Since datasets are too large to upload on Github, the files are uploaded on Google Drive. Download with links below:

• Korean Dataset (brought from BigKinds news data using news-crawler)
• English Dataset (brought from CNN/Dailymail dataset, using cnn-dailymail)
• Korean Pretrained Model
• English Pretrained Model (brought from here)

Dataset location

original: project-root/data/
preprocessed: project-root/src/sum/pgn/data/

Model location

project-root/src/sum/pgn/model/

Note that you have to extract content only. Do not create subdirectory under the location.

The demo page is made with Django framework. To run the demo, try this:

python src/demo/manage.py runserver