Recommender systems in the era of large language models (llms)
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an important component of our daily life, providing personalized suggestions …
have become an important component of our daily life, providing personalized suggestions …
Recommender systems in the era of large language models (llms)
With the prosperity of e-commerce and web applications, Recommender Systems (RecSys)
have become an indispensable and important component in our daily lives, providing …
have become an indispensable and important component in our daily lives, providing …
Trustworthy ai: A computational perspective
In the past few decades, artificial intelligence (AI) technology has experienced swift
developments, changing everyone's daily life and profoundly altering the course of human …
developments, changing everyone's daily life and profoundly altering the course of human …
Diffnet++: A neural influence and interest diffusion network for social recommendation
Social recommendation has emerged to leverage social connections among users for
predicting users' unknown preferences, which could alleviate the data sparsity issue in …
predicting users' unknown preferences, which could alleviate the data sparsity issue in …
A survey of graph neural network based recommendation in social networks
X Li, L Sun, M Ling, Y Peng - Neurocomputing, 2023 - Elsevier
With the widespread popularization of social network platforms, user-generated content and
other social network data are growing rapidly. It is difficult for social users to select interested …
other social network data are growing rapidly. It is difficult for social users to select interested …
Consisrec: Enhancing gnn for social recommendation via consistent neighbor aggregation
Social recommendation aims to fuse social links with user-item interactions to alleviate the
cold-start problem for rating prediction. Recent developments of Graph Neural Networks …
cold-start problem for rating prediction. Recent developments of Graph Neural Networks …
Neighbor interaction aware graph convolution networks for recommendation
Personalized recommendation plays an important role in many online services. Substantial
research has been dedicated to learning embeddings of users and items to predict a user's …
research has been dedicated to learning embeddings of users and items to predict a user's …
Deep learning techniques for recommender systems based on collaborative filtering
Abstract In the Big Data Era, recommender systems perform a fundamental role in data
management and information filtering. In this context, Collaborative Filtering (CF) persists as …
management and information filtering. In this context, Collaborative Filtering (CF) persists as …
Graph trend filtering networks for recommendation
Recommender systems aim to provide personalized services to users and are playing an
increasingly important role in our daily lives. The key of recommender systems is to predict …
increasingly important role in our daily lives. The key of recommender systems is to predict …
Generative diffusion models on graphs: Methods and applications
Diffusion models, as a novel generative paradigm, have achieved remarkable success in
various image generation tasks such as image inpainting, image-to-text translation, and …
various image generation tasks such as image inpainting, image-to-text translation, and …