VRKG4Rec: Virtual Relational Knowledge Graph for Recommendation

This is the PyTorch Implementation for the paper VRKG4Rec (WSDM'23):

Lingyun Lu, Bang Wang, Zizhuo Zhang, Shenghao Liu and Han Xu. VRKG4Rec: Virtual Relational Knowledge Graph for Recommendation.

Introduction

Virtual Relational Knowledge Graph for Recommendation (VRKG4Rec) is a knowledge-aware recommendation framework, which explicitly distinguishes the influence of different relations for item representation learning and design a local weighted smoothing (LWS) mechanism for user and item encoding.

Citation

If you want to use our codes and datasets in your research, please cite:

@inproceedings{10.1145/3539597.3570482,
author = {Lu, Lingyun and Wang, Bang and Zhang, Zizhuo and Liu, Shenghao and Xu, Han},
title = {VRKG4Rec: Virtual Relational Knowledge Graph for Recommendation},
year = {2023},
isbn = {9781450394079},
publisher = {Association for Computing Machinery},
url = {https://doi.org/10.1145/3539597.3570482},
doi = {10.1145/3539597.3570482},
booktitle = {Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining},
series = {WSDM '23}
}

Environment Requirement

The code has been tested running under Python 3.8.0. The required packages are as follows:

• pytorch == 1.10.1
• networkx == 2.5.1
• numpy == 1.22.4
• pandas == 1.4.3
• scikit-learn == 1.1.1
• scipy == 1.7.0
• torch == 1.9.0
• torch-cluster == 1.5.9
• torch-scatter == 2.0.9
• torch-sparse == 0.6.12

Usage

The instruction of commands has been clearly stated in the codes (see the parser function in utils/parser.py).

• Last-fm dataset

python main.py --dataset last-fm --lr 0.0001 --n_virtual 3 --context_hops 2 --n_iter 3

• MovieLens dataset

python main.py --dataset MovieLens --lr 0.0001 --n_virtual 3 --context_hops 2 --n_iter 3

Dataset

We provide three processed datasets: Last-FM and MovieLens.

• You can find the full version of recommendation datasets via Last-FM and MovieLens.
• We follow the previous study to preprocess the datasets.

		Last-FM	MovieLens
User-Item Interaction	#Users	1,872	6,036
	#Items	3,915	2,347
	#Interactions	42,346	753,772
Knowledge Graph	#Entities	9,366	6,729
	#Relations	60	7
	#Triplets	15,518	20,195