When large language models meet personalization: Perspectives of challenges and opportunities
The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …
intelligence. With the unprecedented scale of training and model parameters, the capability …
Network representation learning: A survey
With the widespread use of information technologies, information networks are becoming
increasingly popular to capture complex relationships across various disciplines, such as …
increasingly popular to capture complex relationships across various disciplines, such as …
A survey on knowledge graph-based recommender systems
To solve the information explosion problem and enhance user experience in various online
applications, recommender systems have been developed to model users' preferences …
applications, recommender systems have been developed to model users' preferences …
Multi-level cross-view contrastive learning for knowledge-aware recommender system
Knowledge graph (KG) plays an increasingly important role in recommender systems.
Recently, graph neural networks (GNNs) based model has gradually become the theme of …
Recently, graph neural networks (GNNs) based model has gradually become the theme of …
Knowledge graph convolutional networks for recommender systems
To alleviate sparsity and cold start problem of collaborative filtering based recommender
systems, researchers and engineers usually collect attributes of users and items, and design …
systems, researchers and engineers usually collect attributes of users and items, and design …
Knowledge-aware graph neural networks with label smoothness regularization for recommender systems
Knowledge graphs capture structured information and relations between a set of entities or
items. As such knowledge graphs represent an attractive source of information that could …
items. As such knowledge graphs represent an attractive source of information that could …
Multi-modal knowledge graphs for recommender systems
Recommender systems have shown great potential to solve the information explosion
problem and enhance user experience in various online applications. To tackle data sparsity …
problem and enhance user experience in various online applications. To tackle data sparsity …
Ripplenet: Propagating user preferences on the knowledge graph for recommender systems
To address the sparsity and cold start problem of collaborative filtering, researchers usually
make use of side information, such as social networks or item attributes, to improve …
make use of side information, such as social networks or item attributes, to improve …
Multi-task feature learning for knowledge graph enhanced recommendation
Collaborative filtering often suffers from sparsity and cold start problems in real
recommendation scenarios, therefore, researchers and engineers usually use side …
recommendation scenarios, therefore, researchers and engineers usually use side …
DKN: Deep knowledge-aware network for news recommendation
Online news recommender systems aim to address the information explosion of news and
make personalized recommendation for users. In general, news language is highly …
make personalized recommendation for users. In general, news language is highly …