#RIECN: learning relation-based interactive embedding convolutional network for knowledge graph. This is our Pytorch implementation for the paper:

Introduction

Usage The hyper-parameter search range and optimal settings have been clearly stated in the codes (see the parser function in src/main.py).

Train and Test python main.py

Citation: @article{RIECN, title={RIECN: learning relation-based interactive embedding convolutional network for knowledge graph}, author={Wang, Wei and Shen, Xiaoxuan and Zhang, Huanyu and Li, Zhifei and Yi, Baolin}, journal={Neural Computing and Applications}, volume={35}, number={11}, pages={8343--8356}, year={2023}, publisher={Springer} }