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20192026
most citedElliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

102 citations · 175 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.IR2026

Data Processing for Offline Evaluation in Recommender Systems: a Survey

Alberto Carlo Maria Mancino, Angela Di Fazio, Danilo Danese +5

Offline evaluation is the dominant experimental paradigm in recommender systems research, enabling reproducible and cost-effective comparisons on historical interaction data. Yet,…

cs.IR2024

DataRec: A Python Library for Standardized and Reproducible Data Management in Recommender Systems

Alberto Carlo Maria Mancino, Salvatore Bufi, Angela Di Fazio +4

Recommender systems have demonstrated significant impact across diverse domains, yet ensuring the reproducibility of experimental findings remains a persistent challenge. A primary…

cs.IR2024

KGUF: Simple Knowledge-aware Graph-based Recommender with User-based Semantic Features Filtering

Salvatore Bufi, Alberto Carlo Maria Mancino, Antonio Ferrara +3

The recent integration of Graph Neural Networks (GNNs) into recommendation has led to a novel family of Collaborative Filtering (CF) approaches, namely Graph Collaborative Filterin…

cs.IR2021★ 24 cited

Sparse Feature Factorization for Recommender Systems with Knowledge Graphs

Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio +2

Deep Learning and factorization-based collaborative filtering recommendation models have undoubtedly dominated the scene of recommender systems in recent years. However, despite th…

cs.IR2021★ 102 cited

Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara +5

Recommender Systems have shown to be an effective way to alleviate the over-choice problem and provide accurate and tailored recommendations. However, the impressive number of prop…

cs.IR2021

FedeRank: User Controlled Feedback with Federated Recommender Systems

Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia +2

Recommender systems have shown to be a successful representative of how data availability can ease our everyday digital life. However, data privacy is one of the most prominent con…