
A lightweight Graph Inception Diffusion Network (GIDN) model that generalizes graph diffusion in different feature spaces and uses the inception module to avoid the large computational cost of complex network structures, achieving high-efficiency link prediction.


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gidn-a-lightweight-graph-inception-diffusion-network-for-efficient-link-prediction


GIDN: A Lightweight Graph Inception Diffusion Network for Efficient Link Prediction


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A novel approach that integrates centrality measures with classical machine learning methods to enhance link prediction in knowledge graphs by leveraging the graph's topology through depth-first and breadth-first search techniques.


a-comprehensive-approach-to-link-prediction-in-knowledge-graphs-using-depth-first-and-breadth-first-search-methods


A Comprehensive Approach to Link Prediction in Knowledge Graphs Using Depth-First and Breadth-First Search Methods



지식 그래프에서 깊이 우선 탐색(DFS)과 너비 우선 탐색(BFS)을 결합한 새로운 접근법을 제안하여 링크 예측 성능을 향상시킬 수 있다.


지식-그래프에서의-새로운-dfs-bfs-기반-링크-예측-접근법


지식 그래프에서의 새로운 DFS/BFS 기반 링크 예측 접근법
