Knowledge Graph-Based Socially Enhanced Explainable Recommendation System Introduction With the increasing amount of information in the Internet world, the relevant information about users and products has rapidly expanded, leading to a growing problem of information overload. Recommendation systems can effectively alleviate this problem by recomme...

Knowledge Enhanced Graph Neural Networks for Explainable Recommendation Introduction With the explosive growth of online information, recommendation systems play an essential role in solving the problem of information overload. Traditional recommendation systems typically rely on Collaborative Filtering (CF) methods, which generate recommendations ...

Deep Graph Memory Network for Forgetting-Robust Knowledge Tracing In recent years, Knowledge Tracing (KT) has attracted widespread attention as an important method for personalized learning. The goal of KT is to predict the accuracy of a student’s answers to new questions by utilizing their past answer history to estimate their knowledge state. How...

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 ...

Unified Large Language Models and Knowledge Graphs Background In recent years, numerous research achievements have emerged in the fields of natural language processing and artificial intelligence. Notably, large language models (LLMs) such as ChatGPT and GPT-4 have demonstrated remarkable performance. However, despite their excellent generalization...

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...