Connecting Embeddings Based on Multiplex Relational Graph Attention Networks for Knowledge Graph Entity Typing

Information Science, Computer Science, Artificial Intelligence,
Knowledge Graph   Entity Typing   Graph Attention Networks   Embedding Learning   Multiplex Relational Graph  

Using Connection Embeddings Based on Multi-Relational Graph Attention Networks for Entity Typing in Knowledge Graphs Research Background Today, knowledge graphs (KGs) are garnering increasing research interest in various AI-related fields driven by KGs. Large-scale knowledge graphs provide rich and efficient structured information, serving as core ...

Graph-Based Non-Sampling for Knowledge Graph Enhanced Recommendation

Graph-Based Non-Sampling for Knowledge Graph Enhanced Recommendation

Information Science, Electronic Information, Computer Science, Artificial Intelligence,
Knowledge Graph   Graph Neural Network   Non-Sampling Strategy   Recommendation System   Embedding Learning  

Graph-Based Sampling-Free Knowledge Graph Enhanced Recommendation In recent years, knowledge graph (KG) enhanced recommendation systems, aiming to address cold start problems and the interpretability of recommendation systems, have garnered substantial research interest. Existing recommendation systems typically focus on implicit feedback such as p...

Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph

Information Science, Computer Science, Artificial Intelligence,
Recommendation Systems   Knowledge Graph   Graph Neural Networks   Contextual Information   Biased Random Walk   Recurrent Neural Network   Personalized Preferences  

Knowledge Graph-based Recommendation System: Contextualized Graph Attention Network In recent years, with the explosive growth of online information and content, recommendation systems have become increasingly important in various scenarios such as e-commerce websites and social media platforms. These systems typically aim to provide users with a l...