Reinforcement learning based recommender systems: A survey
Recommender systems (RSs) have become an inseparable part of our everyday lives. They
help us find our favorite items to purchase, our friends on social networks, and our favorite …
help us find our favorite items to purchase, our friends on social networks, and our favorite …
Semantic knowledge graphs for the news: A review
ICT platforms for news production, distribution, and consumption must exploit the ever-
growing availability of digital data. These data originate from different sources and in …
growing availability of digital data. These data originate from different sources and in …
Multi-level recommendation reasoning over knowledge graphs with reinforcement learning
Knowledge graphs (KGs) have been widely used to improve recommendation accuracy. The
multi-hop paths on KGs also enable recommendation reasoning, which is considered a …
multi-hop paths on KGs also enable recommendation reasoning, which is considered a …
Personalized news recommendation: Methods and challenges
Personalized news recommendation is important for users to find interesting news
information and alleviate information overload. Although it has been extensively studied …
information and alleviate information overload. Although it has been extensively studied …
Reinforcement subgraph reasoning for fake news detection
The wide spread of fake news has caused serious societal issues. We propose a subgraph
reasoning paradigm for fake news detection, which provides a crystal type of explainability …
reasoning paradigm for fake news detection, which provides a crystal type of explainability …
Kr-gcn: Knowledge-aware reasoning with graph convolution network for explainable recommendation
T Ma, L Huang, Q Lu, S Hu - ACM Transactions on Information Systems, 2023 - dl.acm.org
Incorporating knowledge graphs (KGs) into recommender systems to provide explainable
recommendation has attracted much attention recently. The multi-hop paths in KGs can …
recommendation has attracted much attention recently. The multi-hop paths in KGs can …
A survey on reinforcement learning for recommender systems
Recommender systems have been widely applied in different real-life scenarios to help us
find useful information. In particular, reinforcement learning (RL)-based recommender …
find useful information. In particular, reinforcement learning (RL)-based recommender …
Knowledge plugins: Enhancing large language models for domain-specific recommendations
The significant progress of large language models (LLMs) provides a promising opportunity
to build human-like systems for various practical applications. However, when applied to …
to build human-like systems for various practical applications. However, when applied to …
Reinforcement routing on proximity graph for efficient recommendation
We focus on Maximum Inner Product Search (MIPS), which is an essential problem in many
machine learning communities. Given a query, MIPS finds the most similar items with the …
machine learning communities. Given a query, MIPS finds the most similar items with the …
Relphormer: Relational graph transformer for knowledge graph representations
Transformers have achieved remarkable performance in widespread fields, including
natural language processing, computer vision and graph mining. However, vanilla …
natural language processing, computer vision and graph mining. However, vanilla …