A Community Detection and Graph-Neural-Network-Based Link Prediction Approach for Scientific Literature
This study presents a novel approach that synergizes community detection algorithms with various Graph Neural Network (GNN) models to bolster link prediction in scientific literature networks. By integrating the Louvain community detection algorithm into our GNN frameworks, we consistently enhanced...
Main Authors: | Chunjiang Liu, Yikun Han, Haiyun Xu, Shihan Yang, Kaidi Wang, Yongye Su |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-01-01
|
Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/12/3/369 |
Similar Items
-
LeL-GNN: Learnable Edge Sampling and Line Based Graph Neural Network for Link Prediction
by: Md Golam Morshed, et al.
Published: (2023-01-01) -
Graph Neural Network-Based Efficient Subgraph Embedding Method for Link Prediction in Mobile Edge Computing
by: Xiaolong Deng, et al.
Published: (2023-05-01) -
Detecting Pseudo-Manipulated Citations in Scientific Literature through Perturbations of the Citation Graph
by: Renata Avros, et al.
Published: (2023-09-01) -
Learning Heterogeneous Graph Embedding with Metapath-Based Aggregation for Link Prediction
by: Chengdong Zhang, et al.
Published: (2023-01-01) -
Link prediction in paper citation network to construct paper correlation graph
by: Hanwen Liu, et al.
Published: (2019-10-01)