Author

Antonio Ferrara

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Book Open access Oct 2026

Distribution-Robust Reranking for Conversational Music Recommendation: PoliBaJukebox at the ACM RecSys Challenge 2026

We describe the PoliBaJukebox submission to the ACM RecSys Challenge 2026 on conversational music recommendation over the TalkPlayData 2 corpus. Our system implements a modular two-stage pipeline: a first stage retrieves candidates from the full track catalog using ten heterogeneous sources, fuses them with weighted Re...

Andrea Lops, Nicola Cipriani, Gabriele Colapinto et al. · Proceedings of the Workshop... · 1 citation

Open access 2026

Derivative-Free Emergent Optimization via Local Rules and Cellular Automata

We introduce the Cellular Direct Search (CDS), a derivative-free optimization method inspired by the emergent dynamics of Cellular Automata. CDS partitions the parameter space into a discrete grid where a population of agents evolves according to strictly local rules: a Jealous Neighbor Rule for competitive selection a...

Antonio Ferrara, Giuseppe Mariano Balducci, Tommaso Di Noia · IEEE Access · 0 citations

#machine learning Review Sep 2026

Data Processing for Offline Evaluation in Recommender Systems: a Survey

A systematic, cross-domain characterisation of data processing practices for the offline evaluation of recommender systems is provided, identifying substantial heterogeneity in how auxiliary information is prepared and represented, as well as inconsistencies in the specification of data splitting protocols.

Alberto Carlo Maria Mancino, Angela Di Fazio, Danilo Danese et al. · 0 citations

#graph neural networks Book Open access Oct 2026

Beyond Single-Signal Retrieval: A Graph-Aware Agentic Framework for Conversational Music Recommendation

Experimental results show the pipeline outperforms baselines in ranking, diversity, and explanations, proving that combining graph embeddings with agentic reasoning successfully bridges long-term profiles and immediate intent.

Marco Valentini, Bianca Di Bitetto, Gianmichele De Palma et al. · Proceedings of the Workshop... · 1 citation

Open access Jul 2026

AMIUgraph: analysis and modeling of interactions for utility-driven benchmarking of graph-based models in healthcare.

AMIUGraph provides a clinically grounded and utility-driven benchmarking framework that jointly evaluates KGE and GNN models across multiple healthcare graph types and learning settings, and offers practical guidance for selecting graph-based models in medical decision-support systems.

P. Sorino, A. D. Bellis, Daniele Malitesta et al. · BMC Medical Informatics and... · 0 citations