QDN-A-Quadruplet-Distributor-Network-for-Temporal-Knowledge-Graph-Completion

Installation

Create a conda environment with pytorch and scikit-learn :

conda create --name QDN_env python=3.7
source activate QDN_env
conda install --file requirements.txt -c pytorch

Then install the kbc package to this environment

python setup.py install

Datasets

Once the datasets are downloaded, go to the tkbc/ folder and add them to the package data folder by running :

python process_icews.py

This will create the files required to compute the filtered metrics.

Reproducing results of QDN

In order to reproduce the results of QDN on the four datasets in the paper, go to the tkbc/ folder and run the following commands

python learner.py --dataset ICEWS14 --model TeLM --rank 2000 --emb_reg 0.0075 --time_reg 0.01 

python learner.py --dataset ICEWS05-15 --model TeLM --rank 2000 --emb_reg 0.0025 --time_reg 0.1