Claudio Pomo

82 papers A* 4A 14B 1Journal 34Unranked 27
YearRankTypeTitle / Venue / Authors
2026 — conf
A Reproducible and Fair Evaluation of Partition-Aware Collaborative Filtering.
ECIR (3)
Domenico de Gioia, Claudio Pomo, Ludovico Boratto, Tommaso Di Noia
2026 J jnl
Large-scale benchmarks for multimodal recommendation with Ducho.
Expert Syst. Appl.
Matteo Attimonelli, Danilo Danese, Angela Di Fazio, Daniele Malitesta, Claudio Pomo, Tommaso Di Noia
2026 — ed.
Proceedings of the DaQuaMRec 2025 Workshop on Data Quality-Aware Multimodal Recommendation co-located with RecSys 2025, Prague, Czech Republic, September 22, 2025.
DaQuaMRec@RecSys
Claudio Pomo, Dietmar Jannach, Yubin Kim, Daniele Malitesta, Alberto Carlo Maria Mancino, Julian J. McAuley, Alessandro B. Melchiorre, Shah Nawaz
2026 J jnl
Training-Free Graph-Based Imputation of Missing Modalities in Multimodal Recommendation.
IEEE Trans. Knowl. Data Eng.
Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros
2026 J jnl
Training-free Graph-based Imputation of Missing Modalities in Multimodal Recommendation.
CoRR
Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros
2025 J jnl
A Reproducible and Fair Evaluation of Partition-aware Collaborative Filtering.
CoRR
Domenico de Gioia, Claudio Pomo, Ludovico Boratto, Tommaso Di Noia
2025 A* conf
DataRec: A Python Library for Standardized and Reproducible Data Management in Recommender Systems.
SIGIR
Alberto Carlo Maria Mancino, Salvatore Bufi, Angela Di Fazio, Antonio Ferrara, Daniele Malitesta, Claudio Pomo, Tommaso Di Noia
2025 A conf
Do Recommender Systems Really Leverage Multimodal Content? A Comprehensive Analysis on Multimodal Representations for Recommendation.
CIKM
Claudio Pomo, Matteo Attimonelli, Danilo Danese, Fedelucio Narducci, Tommaso Di Noia
2025 J jnl
Do Recommender Systems Really Leverage Multimodal Content? A Comprehensive Analysis on Multimodal Representations for Recommendation.
CoRR
Claudio Pomo, Matteo Attimonelli, Danilo Danese, Fedelucio Narducci, Tommaso Di Noia
2025 A conf
Do We Really Need Specialization? Evaluating Generalist Text Embeddings for Zero-Shot Recommendation and Search.
RecSys
Matteo Attimonelli, Alessandro De Bellis, Claudio Pomo, Dietmar Jannach, Eugenio Di Sciascio, Tommaso Di Noia
2025 J jnl
Do We Really Need Specialization? Evaluating Generalist Text Embeddings for Zero-Shot Recommendation and Search.
CoRR
Matteo Attimonelli, Alessandro De Bellis, Claudio Pomo, Dietmar Jannach, Eugenio Di Sciascio, Tommaso Di Noia
2025 — conf
Enhancing News Recommendation Systems Using Multitask Learning.
UMAP (Adjunct Publication)
Paolo Masciullo, Andrea Pazienza, Claudio Pomo, Fedelucio Narducci, Tommaso Di Noia
2025 — conf
Enhancing Reproducibility and Replicability in Information Retrieval: A Path Towards Scientific Integrity and Effective Research.
ECIR (5)
Antonio Ferrara, Claudio Pomo, Nicola Tonellotto
2025 B conf
Enhancing Reproducibility and Replicability in Information Retrieval: A Path Towards Scientific Integrity and Effective Research.
ICWE
Antonio Ferrara, Claudio Pomo, Nicola Tonellotto
2025 A conf
First International Workshop on Data Quality-Aware Multimodal Recommendation (DaQuaMRec).
RecSys
Claudio Pomo, Dietmar Jannach, Yubin Kim, Daniele Malitesta, Alberto Carlo Maria Mancino, Julian J. McAuley, Alessandro B. Melchiorre, Shah Nawaz
2025 J jnl
Formalizing Multimedia Recommendation through Multimodal Deep Learning.
Trans. Recomm. Syst.
Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo, Felice Antonio Merra, Tommaso Di Noia, Eugenio Di Sciascio
2025 A conf
How Powerful are LLMs to Support Multimodal Recommendation? A Reproducibility Study of LLMRec.
RecSys
Maria Lucia Fioretti, Nicola Laterza, Alessia Preziosa, Daniele Malitesta, Claudio Pomo, Fedelucio Narducci, Tommaso Di Noia
2025 J jnl
On the Impact of Graph Neural Networks in Recommender Systems: A Topological Perspective.
CoRR
Daniele Malitesta, Claudio Pomo, Vito Walter Anelli, Alberto Carlo Maria Mancino, Alejandro Bellogín, Tommaso Di Noia
2025 A conf
RecSys Challenge 2025: Universal Behavioral Profiles for Recommender Systems.
RecSys
Jacek Dabrowski, Maria Janicka, Lukasz Sienkiewicz, Gergely Stomfai, Dietmar Jannach, Francesco Barile, Marco Polignano, Claudio Pomo, Abhishek Srivastava
2024 A conf
A Novel Evaluation Perspective on GNNs-based Recommender Systems through the Topology of the User-Item Graph.
RecSys
Daniele Malitesta, Claudio Pomo, Vito Walter Anelli, Alberto Carlo Maria Mancino, Tommaso Di Noia, Eugenio Di Sciascio
2024 J jnl
A Novel Evaluation Perspective on GNNs-based Recommender Systems through the Topology of the User-Item Graph.
CoRR
Daniele Malitesta, Claudio Pomo, Vito Walter Anelli, Alberto Carlo Maria Mancino, Tommaso Di Noia, Eugenio Di Sciascio
2024 J jnl
A qualitative analysis of knowledge graphs in recommendation scenarios through semantics-aware autoencoders.
J. Intell. Inf. Syst.
Vito Bellini, Eugenio Di Sciascio, Francesco Maria Donini, Claudio Pomo, Azzurra Ragone, Angelo Schiavone
2024 — conf
DIVAN: Deep-Interest Virality-Aware Network to Exploit Temporal Dynamics in News Recommendation.
RecSys Challenge
Antonio Ferrara, Marco Valentini, Paolo Masciullo, Antonio De Candia, Davide Abbattista, Riccardo Fusco, Claudio Pomo, Vito Walter Anelli, Giovanni Maria Biancofiore, Ludovico Boratto, Fedelucio Narducci
2024 J jnl
DataRec: A Framework for Standardizing Recommendation Data Processing and Analysis.
CoRR
Alberto Carlo Maria Mancino, Salvatore Bufi, Angela Di Fazio, Daniele Malitesta, Claudio Pomo, Antonio Ferrara, Tommaso Di Noia
2024 J jnl
Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach.
CoRR
Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Fragkiskos D. Malliaros, Tommaso Di Noia
2024 A conf
Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation?
CIKM
Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros
2024 J jnl
Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation?
CoRR
Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros
2024 — conf
Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation.
WWW (Companion Volume)
Matteo Attimonelli, Danilo Danese, Daniele Malitesta, Claudio Pomo, Giuseppe Gassi, Tommaso Di Noia
2024 J jnl
Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation.
CoRR
Matteo Attimonelli, Danilo Danese, Daniele Malitesta, Claudio Pomo, Giuseppe Gassi, Tommaso Di Noia
2024 J jnl
Ducho meets Elliot: Large-scale Benchmarks for Multimodal Recommendation.
CoRR
Matteo Attimonelli, Danilo Danese, Angela Di Fazio, Daniele Malitesta, Claudio Pomo, Tommaso Di Noia
2024 — conf
EB-NeRD a large-scale dataset for news recommendation.
RecSys Challenge
Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen
2024 J jnl
EB-NeRD: A Large-Scale Dataset for News Recommendation.
CoRR
Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen
2024 J jnl
Fashion Image-to-Image Translation for Complementary Item Retrieval.
CoRR
Matteo Attimonelli, Claudio Pomo, Dietmar Jannach, Tommaso Di Noia
2024 A conf
RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations.
RecSys
Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen
2024 J jnl
RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations.
CoRR
Johannes Kruse, Kasper Lindskow, Saikishore Kalloori, Marco Polignano, Claudio Pomo, Abhishek Srivastava, Anshuk Uppal, Michael Riis Andersen, Jes Frellsen
2024 — conf
Toward Effective Fashion Item Compatibility Modelling.
IIR
Matteo Attimonelli, Claudio Pomo, Dietmar Jannach, Tommaso Di Noia
2023 J jnl
A Topology-aware Analysis of Graph Collaborative Filtering.
CoRR
Daniele Malitesta, Claudio Pomo, Vito Walter Anelli, Alberto Carlo Maria Mancino, Eugenio Di Sciascio, Tommaso Di Noia
2023 — conf
An Out-of-the-Box Application for Reproducible Graph Collaborative Filtering extending the Elliot Framework.
UMAP (Adjunct Publication)
Daniele Malitesta, Claudio Pomo, Vito Walter Anelli, Tommaso Di Noia, Antonio Ferrara
2023 — conf
Auditing Consumer- and Producer-Fairness in Graph Collaborative Filtering.
ECIR (1)
Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta, Vincenzo Paparella, Claudio Pomo
2023 J jnl
Auditing fairness under unawareness through counterfactual reasoning.
Inf. Process. Manag.
Giandomenico Cornacchia, Vito Walter Anelli, Giovanni Maria Biancofiore, Fedelucio Narducci, Claudio Pomo, Azzurra Ragone, Eugenio Di Sciascio
2023 A conf
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis.
RecSys
Vito Walter Anelli, Daniele Malitesta, Claudio Pomo, Alejandro Bellogín, Eugenio Di Sciascio, Tommaso Di Noia
2023 J jnl
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis.
CoRR
Vito Walter Anelli, Daniele Malitesta, Claudio Pomo, Alejandro Bellogín, Tommaso Di Noia, Eugenio Di Sciascio
2023 — conf
Disentangling the Performance Puzzle of Multimodal-aware Recommender Systems.
EvalRS@KDD
Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo, Tommaso Di Noia
2023 A* conf
Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation.
ACM Multimedia
Daniele Malitesta, Giuseppe Gassi, Claudio Pomo, Tommaso Di Noia
2023 J jnl
Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation.
CoRR
Daniele Malitesta, Giuseppe Gassi, Claudio Pomo, Tommaso Di Noia
2023 J jnl
EvalRS 2023. Well-Rounded Recommender Systems For Real-World Deployments.
CoRR
Federico Bianchi, Patrick John Chia, Ciro Greco, Claudio Pomo, Gabriel de Souza P. Moreira, Davide Eynard, Fahd Husain, Jacopo Tagliabue
2023 A* conf
EvalRS 2023: Well-Rounded Recommender Systems for Real-World Deployments.
KDD
Federico Bianchi, Patrick John Chia, Jacopo Tagliabue, Ciro Greco, Gabriel de Souza P. Moreira, Davide Eynard, Fahd Husain, Claudio Pomo
2023 — conf
Examining Fairness in Graph-Based Collaborative Filtering: A Consumer and Producer Perspective.
IIR
Dario Di Palma, Vito Walter Anelli, Daniele Malitesta, Vincenzo Paparella, Claudio Pomo, Yashar Deldjoo, Tommaso Di Noia
2023 J jnl
Formalizing Multimedia Recommendation through Multimodal Deep Learning.
CoRR
Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo, Felice Antonio Merra, Tommaso Di Noia, Eugenio Di Sciascio
2023 J jnl
Graph Neural Networks for Recommendation: Reproducibility, Graph Topology, and Node Representation.
CoRR
Daniele Malitesta, Claudio Pomo, Tommaso Di Noia
2023 — conf
Irrelevant Explanations: a Logical Formalization and a Case Study.
XAI.it@AI*IA
Simona Colucci, Tommaso Di Noia, Francesco M. Donini, Claudio Pomo, Eugenio Di Sciascio
2023 — conf
Knowledge Graph Datasets for Recommendation.
KaRS@RecSys
Vincenzo Paparella, Alberto Carlo Maria Mancino, Antonio Ferrara, Claudio Pomo, Vito Walter Anelli, Tommaso Di Noia
2023 — conf
On Popularity Bias of Multimodal-aware Recommender Systems: A Modalities-driven Analysis.
MMIR@MM
Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo, Tommaso Di Noia
2023 J jnl
On Popularity Bias of Multimodal-aware Recommender Systems: a Modalities-driven Analysis.
CoRR
Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo, Tommaso Di Noia
2023 — ed.
Proceedings of EvalRS: A Rounded Evaluation Of Recommender Systems 2023 co-located with 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2023), Long Beach,CA, USA, August 7, 2023.
EvalRS@KDD
Federico Bianchi, Patrick John Chia, Ciro Greco, Claudio Pomo, Gabriel de Souza P. Moreira, Davide Eynard, Fahd Husain, Jacopo Tagliabue
2022 — conf
An Analysis of Local Explanation with LIME-RS.
IIR
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo
2022 J jnl
Conversational recommendation: Theoretical model and complexity analysis.
Inf. Sci.
Tommaso Di Noia, Francesco Maria Donini, Dietmar Jannach, Fedelucio Narducci, Claudio Pomo
2022 — conf
How Neighborhood Exploration influences Novelty and Diversity in Graph Collaborative Filtering.
MORS@RecSys
Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Daniele Malitesta, Claudio Pomo
2022 — conf
Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews.
DL4SR@CIKM
Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Daniele Malitesta, Claudio Pomo
2022 — conf
The Challenging Reproducibility Task in Recommender Systems Research between Traditional and Deep Learning Models.
SEBD
Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco M. Donini, Eugenio Di Sciascio, Tommaso Di Noia
2022 A conf
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art.
UMAP
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Dietmar Jannach, Claudio Pomo
2022 J jnl
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art.
CoRR
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Dietmar Jannach, Claudio Pomo
2022 — conf
Towards a theoretical formalization of conversational recommendation.
CIKM Workshops
Tommaso Di Noia, Francesco Maria Donini, Dietmar Jannach, Fedelucio Narducci, Claudio Pomo
2021 — conf
Adherence and Constancy in LIME-RS Explanations for Recommendation (Long paper).
KaRS/ComplexRec@RecSys
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo
2021 J jnl
Adherence and Constancy in LIME-RS Explanations for Recommendation.
CoRR
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo
2021 J jnl
Conversational Recommendation: Theoretical Model and Complexity Analysis.
CoRR
Tommaso Di Noia, Francesco M. Donini, Dietmar Jannach, Fedelucio Narducci, Claudio Pomo
2021 A* conf
Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation.
SIGIR
Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco Maria Donini, Tommaso Di Noia
2021 J jnl
Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation.
CoRR
Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco M. Donini, Tommaso Di Noia
2021 — conf
Explanation in Multi-Stakeholder Recommendation for Enterprise Decision Support Systems.
CAiSE Workshops
Giandomenico Cornacchia, Francesco M. Donini, Fedelucio Narducci, Claudio Pomo, Azzurra Ragone
2021 — conf
How to Perform Reproducible Experiments in the ELLIOT Recommendation Framework: Data Processing, Model Selection, and Performance Evaluation.
IIR
Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco Maria Donini, Eugenio Di Sciascio, Tommaso Di Noia
2021 — conf
On the Need for a Body of Knowledge on Recommender Systems (Short paper).
KaRS/ComplexRec@RecSys
Juri Di Rocco, Davide Di Ruscio, Claudio Di Sipio, Phuong Thanh Nguyen, Claudio Pomo
2021 A conf
Pursuing Privacy in Recommender Systems: the View of Users and Researchers from Regulations to Applications.
RecSys
Vito Walter Anelli, Luca Belli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara, Fedelucio Narducci, Claudio Pomo
2021 J jnl
Reenvisioning Collaborative Filtering vs Matrix Factorization.
CoRR
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Claudio Pomo
2021 A conf
Reenvisioning the comparison between Neural Collaborative Filtering and Matrix Factorization.
RecSys
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Claudio Pomo
2021 A conf
V-Elliot: Design, Evaluate and Tune Visual Recommender Systems.
RecSys
Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco Maria Donini, Tommaso Di Noia
2020 — conf
GUapp: A Conversational Agent for Job Recommendation for the Italian Public Administration.
EAIS
Vito Bellini, Giovanni Maria Biancofiore, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci, Claudio Pomo
2020 — conf
Towards a Trustworthy Patient Home-Care Thanks to an Edge-Node Infrastructure.
HCSE
Carmelo Ardito, Tommaso Di Noia, Eugenio Di Sciascio, Domenico Lofù, Giulio Mallardi, Claudio Pomo, Felice Vitulano
2019 J jnl
On the discriminative power of Hyper-parameters in Cross-Validation and how to choose them.
CoRR
Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Claudio Pomo, Azzurra Ragone
2019 A conf
On the discriminative power of hyper-parameters in cross-validation and how to choose them.
RecSys
Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Claudio Pomo, Azzurra Ragone
2019 — conf
Semantic interpretability of latent factors for recommendation.
IIR
Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Azzurra Ragone, Claudio Pomo
2018 J jnl
On fast prototyping LoRaWAN: a cheap and open platform for daily experiments.
IET Wirel. Sens. Syst.
Mariano Pulpito, Paolo Fornarelli, Claudio Pomo, Pietro Boccadoro, Luigi Alfredo Grieco
2017 — conf
Four Key Factors to Design a Web of Things Architecture.
ICWE Workshops
Francesco Bruni, Claudio Pomo, Gaetano Murgolo