117 citations · 658 across the 80 of their papers we have counts for
11 papers · 1 filter
Graph Neural Networks for Recommendation: Reproducibility, Graph Topology, and Node Representation
Daniele Malitesta, Claudio Pomo, Tommaso Di Noia
Graph neural networks (GNNs) have gained prominence in recommendation systems in recent years. By representing the user-item matrix as a bipartite and undirected graph, GNNs have d…
Formalizing Multimedia Recommendation through Multimodal Deep Learning
Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo +3
Recommender systems (RSs) offer personalized navigation experiences on online platforms, but recommendation remains a challenging task, particularly in specific scenarios and domai…
Evaluating ChatGPT as a Recommender System: A Rigorous Approach
Dario Di Palma, Giovanni Maria Biancofiore, Vito Walter Anelli +3
Large Language Models (LLMs) have recently shown impressive abilities in handling various natural language-related tasks. Among different LLMs, current studies have assessed ChatGP…
On Popularity Bias of Multimodal-aware Recommender Systems: a Modalities-driven Analysis
Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo +1
Multimodal-aware recommender systems (MRSs) exploit multimodal content (e.g., product images or descriptions) as items' side information to improve recommendation accuracy. While m…
ChatGPT-HealthPrompt. Harnessing the Power of XAI in Prompt-Based Healthcare Decision Support using ChatGPT
Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia
This study presents an innovative approach to the application of large language models (LLMs) in clinical decision-making, focusing on OpenAI's ChatGPT. Our approach introduces the…
A Topology-aware Analysis of Graph Collaborative Filtering
Daniele Malitesta, Claudio Pomo, Vito Walter Anelli +3
The successful integration of graph neural networks into recommender systems (RSs) has led to a novel paradigm in collaborative filtering (CF), graph collaborative filtering (graph…