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ORCIDTommaso Di Noia
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- affiliation: Polytechnic University of Bari, Italy
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2020 – today
- 2024
[j55]Tommaso Colafiglio, Carmelo Ardito, Paolo Sorino, Domenico Lofù
, Fabrizio Festa, Tommaso Di Noia, Eugenio Di Sciascio:
NeuralPMG: A Neural Polyphonic Music Generation System Based on Machine Learning Algorithms. Cogn. Comput. 16(5): 2779-2802 (2024)- [j54]Yashar Deldjoo, Fatemeh Nazary, Arnau Ramisa, Julian J. McAuley, Giovanni Pellegrini, Alejandro Bellogín, Tommaso Di Noia:
A Review of Modern Fashion Recommender Systems. ACM Comput. Surv. 56(4): 87:1-87:37 (2024) - [j53]Giovanni Maria Biancofiore, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci:
Interactive Question Answering Systems: Literature Review. ACM Comput. Surv. 56(9): 239:1-239:38 (2024) - [c259]Angela Lombardi, Sofia Marzo, Eugenio Di Sciascio, Tommaso Di Noia, Carmelo Ardito:
Intuitiveness and Trustworthiness of AI-Powered Interfaces for Neurological Diagnosis - Preliminary Results. HCSE 2024: 273-280 - [c258]Tommaso Di Noia, Guglielmo Faggioli, Marco Ferrante, Nicola Ferro, Fedelucio Narducci, Raffaele Perego, Giuseppe Santucci:
CAMEO: Fostering Joint Conversational Search and Recommendation. SEBD 2024: 290-301 - [c257]Tommaso Colafiglio, Domenico Lofù, Paolo Sorino, Angela Lombardi, Fedelucio Narducci, Fabrizio Festa, Tommaso Di Noia:
EmoSynth Real Time Emotion-Driven Sound Texture Synthesis via Brain-Computer Interface. UMAP (Adjunct Publication) 2024 - [c256]Tommaso Colafiglio, Tommaso Di Noia, Domenico Lofù, Angela Lombardi, Fedelucio Narducci, Paolo Sorino:
Wearable Devices and Brain-Computer Interfaces for User Modelling (WeBIUM). UMAP (Adjunct Publication) 2024 - [c255]Angela Lombardi, Sofia Marzo, Tommaso Di Noia, Eugenio Di Sciascio, Carmelo Ardito:
Exploring the Usability and Trustworthiness of AI-Driven User Interfaces for Neurological Diagnosis. UMAP (Adjunct Publication) 2024 - [c254]Paolo Sorino, Giovanni Maria Biancofiore, Domenico Lofù, Tommaso Colafiglio, Angela Lombardi, Fedelucio Narducci, Tommaso Di Noia:
ARIEL: Brain-Computer Interfaces meet Large Language Models for Emotional Support Conversation. UMAP (Adjunct Publication) 2024 - [c253]Matteo Attimonelli, Danilo Danese, Daniele Malitesta, Claudio Pomo, Giuseppe Gassi, Tommaso Di Noia:
Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation. WWW (Companion Volume) 2024: 1075-1078 - [i43]Matteo Attimonelli, Danilo Danese, Daniele Malitesta, Claudio Pomo, Giuseppe Gassi, Tommaso Di Noia:
Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation. CoRR abs/2403.04503 (2024) - [i42]Yashar Deldjoo, Tommaso Di Noia:
CFaiRLLM: Consumer Fairness Evaluation in Large-Language Model Recommender System. CoRR abs/2403.05668 (2024) - [i41]Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Fragkiskos D. Malliaros, Tommaso Di Noia:
Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach. CoRR abs/2403.19841 (2024) - [i40]Salvatore Bufi, Alberto Carlo Maria Mancino, Antonio Ferrara, Daniele Malitesta, Tommaso Di Noia, Eugenio Di Sciascio:
KGUF: Simple Knowledge-aware Graph-based Recommender with User-based Semantic Features Filtering. CoRR abs/2403.20095 (2024) - [i39]Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio:
XAI4LLM. Let Machine Learning Models and LLMs Collaborate for Enhanced In-Context Learning in Healthcare. CoRR abs/2405.06270 (2024) - 2023
- [j52]Angela Lombardi, Francesca Arezzo, Eugenio Di Sciascio, Carmelo Ardito, Michele Mongelli, Nicola Di Lillo, Fabiana Divina Fascilla, Erica Silvestris, Anila Kardhashi, Carmela Putino, Ambrogio Cazzolla, Vera Loizzi, Gerardo Cazzato, Gennaro Cormio, Tommaso Di Noia:
A human-interpretable machine learning pipeline based on ultrasound to support leiomyosarcoma diagnosis. Artif. Intell. Medicine 146: 102697 (2023) - [j51]Tommaso Di Noia, In-Young Ko, Markus Schedl:
Introduction to the ICWE 2022 Special Issue. J. Web Eng. 22(1): v-viii (2023) - [j50]Antonio Ferrara, Vito Walter Anelli, Alberto Carlo Maria Mancino, Tommaso Di Noia, Eugenio Di Sciascio:
KGFlex: Efficient Recommendation with Sparse Feature Factorization and Knowledge Graphs. Trans. Recomm. Syst. 1(4): 1-30 (2023) - [c252]Adam Przybylek, Aleksandra Karpus, Allel Hadjali, Anton Dignös, Carmem S. Hara, Danae Pla Karidi, Ester Zumpano, Fabio Persia, Genoveva Vargas-Solar, George Papastefanatos, Giancarlo Sperlì, Giorgos Giannopoulos, Ivan Lukovic, Julien Aligon, Manolis Terrovitis, Marek Grzegorowski, Mariella Bonomo, Mirian Halfeld Ferrari Alves, Nicolas Labroche, Paul Monsarrat, Richard Chbeir, Sana Sellami, Seshu Tirupathi, Simona E. Rombo, Slavica Kordic, Sonja Ristic, Tommaso Di Noia, Torben Bach Pedersen, Vincenzo Moscato:
Databases and Information Systems: Contributions from ADBIS 2023 Workshops and Doctoral Consortium. ADBIS (Short Papers) 2023: 293-311 - [c251]Simona Colucci, Tommaso Di Noia, Francesco M. Donini, Claudio Pomo, Eugenio Di Sciascio:
Irrelevant Explanations: a Logical Formalization and a Case Study. XAI.it@AI*IA 2023: 67-75 - [c250]Vincenzo Paparella, Vito Walter Anelli, Franco Maria Nardini, Raffaele Perego, Tommaso Di Noia:
Post-hoc Selection of Pareto-Optimal Solutions in Search and Recommendation. CIKM 2023: 2013-2023 - [c249]Angela Lombardi, Maria Luigia Natalia De Bonis, Giuseppe Fasano, Alessia Sportelli, Tommaso Colafiglio, Domenico Lofù, Paolo Sorino, Fedelucio Narducci, Eugenio Di Sciascio, Tommaso Di Noia:
Time-to-Event Interpretable Machine Learning for Multiple Sclerosis Worsening Prediction: Results from iDPP@CLEF 2023. CLEF (Working Notes) 2023: 1272-1285 - [c248]Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia:
ChatGPT-HealthPrompt. Harnessing the Power of XAI in Prompt-Based Healthcare Decision Support using ChatGPT. ECAI Workshops (1) 2023: 382-397 - [c247]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta, Vincenzo Paparella, Claudio Pomo:
Auditing Consumer- and Producer-Fairness in Graph Collaborative Filtering. ECIR (1) 2023: 33-48 - [c246]Potito Aghilar, Vito Walter Anelli, Michelantonio Trizio, Tommaso Di Noia:
Scalable Cloud-Native Pipeline for Efficient 3D Model Reconstruction from Monocular Smartphone Images. ECSA 2023: 266-282 - [c245]Tommaso Colafiglio, Domenico Lofù, Paolo Sorino, Fabrizio Festa, Tommaso Di Noia, Eugenio Di Sciascio:
Exploring the Mental State Intersection by Brain-Computer Interfaces, Cellular Automata and Biofeedback. EUROCON 2023: 461-466 - [c244]Dario Di Palma, Vito Walter Anelli, Daniele Malitesta, Vincenzo Paparella, Claudio Pomo, Yashar Deldjoo, Tommaso Di Noia:
Examining Fairness in Graph-Based Collaborative Filtering: A Consumer and Producer Perspective. IIR 2023: 79-84 - [c243]Tommaso Colafiglio, Paolo Sorino, Angela Lombardi, Domenico Lofù, Tommaso Di Noia:
Predicting Human Emotions using EEG-based Brain computer Interface and Interpretable Machine Learning. Ital-IA 2023: 200-205 - [c242]Vito Walter Anelli, Eros Brienza, Marco Recupero, Francesco Greco, Andrea De Maria, Tommaso Di Noia, Eugenio Di Sciascio:
Navigating the Legal Landscape: Developing Italy's Official Legal Knowledge Graph for Enhanced Legislative and Public Services. Ital-IA 2023: 223-228 - [c241]Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia, Carmelo Ardito, Eugenio Di Sciascio:
Smart Electrical Grids Under the Lens of Adversarial Attacks. Ital-IA 2023: 616-621 - [c240]Vincenzo Paparella, Alberto Carlo Maria Mancino, Antonio Ferrara, Claudio Pomo, Vito Walter Anelli, Tommaso Di Noia:
Knowledge Graph Datasets for Recommendation. KaRS@RecSys 2023: 109-117 - [c239]Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo, Tommaso Di Noia:
Disentangling the Performance Puzzle of Multimodal-aware Recommender Systems. EvalRS@KDD 2023 - [c238]Daniele Malitesta, Giuseppe Gassi, Claudio Pomo, Tommaso Di Noia:
Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation. ACM Multimedia 2023: 9668-9671 - [c237]Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo, Tommaso Di Noia:
On Popularity Bias of Multimodal-aware Recommender Systems: A Modalities-driven Analysis. MMIR@MM 2023: 59-68 - [c236]Vito Walter Anelli, Daniele Malitesta, Claudio Pomo, Alejandro Bellogín, Eugenio Di Sciascio, Tommaso Di Noia:
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis. RecSys 2023: 350-361 - [c235]Vincenzo Paparella, Vito Walter Anelli, Ludovico Boratto, Tommaso Di Noia:
Reproducibility of Multi-Objective Reinforcement Learning Recommendation: Interplay between Effectiveness and Beyond-Accuracy Perspectives. RecSys 2023: 467-478 - [c234]Alberto Carlo Maria Mancino, Antonio Ferrara, Salvatore Bufi, Daniele Malitesta, Tommaso Di Noia, Eugenio Di Sciascio:
KGTORe: Tailored Recommendations through Knowledge-aware GNN Models. RecSys 2023: 576-587 - [c233]Vincenzo Paparella, Dario Di Palma, Vito Walter Anelli, Tommaso Di Noia:
Broadening the Scope: Evaluating the Potential of Recommender Systems beyond prioritizing Accuracy. RecSys 2023: 1139-1145 - [c232]Alessandro De Bellis, Giovanni Maria Biancofiore, Vito Walter Anelli, Fedelucio Narducci, Tommaso Di Noia, Azzurra Ragone, Eugenio Di Sciascio:
Semantic Interpretation of BERT Embeddings with Knowledge Graphs. SEBD 2023: 181-191 - [c231]Felice Antonio Merra, Vito Walter Anelli, Tommaso Di Noia, Daniele Malitesta, Alberto Carlo Maria Mancino:
Denoise to Protect: A Method to Robustify Visual Recommenders from Adversaries. SIGIR 2023: 1924-1928 - [c230]Paolo Sorino, Vincenzo Paparella, Domenico Lofù, Tommaso Colafiglio, Eugenio Di Sciascio, Fedelucio Narducci, Rodolfo Sardone, Tommaso Di Noia:
A Pareto-Optimality-Based Approach for Selecting the Best Machine Learning Models in Mild Cognitive Impairment Prediction. SMC 2023: 3822-3827 - [c229]Tommaso Colafiglio, Paolo Sorino, Domenico Lofù, Angela Lombardi, Fedelucio Narducci, Tommaso Di Noia:
Combining Mental States Recognition and Machine Learning for Neurorehabilitation. SMC 2023: 3848-3853 - [c228]Daniele Malitesta, Claudio Pomo, Vito Walter Anelli, Tommaso Di Noia, Antonio Ferrara:
An Out-of-the-Box Application for Reproducible Graph Collaborative Filtering extending the Elliot Framework. UMAP (Adjunct Publication) 2023: 12-15 - [e15]Jie Zhang, Li Chen, Shlomo Berkovsky, Min Zhang, Tommaso Di Noia, Justin Basilico, Luiz Pizzato, Yang Song:
Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023, Singapore, Singapore, September 18-22, 2023. ACM 2023 [contents] - [i38]Domenico Lofù, Paolo Sorino, Tommaso Colafiglio, Caterina Bonfiglio, Fedelucio Narducci, Tommaso Di Noia, Eugenio Di Sciascio:
MAFUS: a Framework to predict mortality risk in MAFLD subjects. CoRR abs/2301.06908 (2023) - [i37]Carmelo Ardito, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fatemeh Nazary, Giovanni Servedio:
Machine-learned Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grids. CoRR abs/2303.18136 (2023) - [i36]Vincenzo Paparella, Vito Walter Anelli, Franco Maria Nardini, Raffaele Perego, Tommaso Di Noia:
Post-hoc Selection of Pareto-Optimal Solutions in Search and Recommendation. CoRR abs/2306.12165 (2023) - [i35]Daniele Malitesta, Giuseppe Gassi, Claudio Pomo, Tommaso Di Noia:
Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation. CoRR abs/2306.17125 (2023) - [i34]Vito Walter Anelli, Daniele Malitesta, Claudio Pomo, Alejandro Bellogín, Tommaso Di Noia, Eugenio Di Sciascio:
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis. CoRR abs/2308.00404 (2023) - [i33]Fatemeh Nazary, Yashar Deldjoo, Tommaso Di Noia:
ChatGPT-HealthPrompt. Harnessing the Power of XAI in Prompt-Based Healthcare Decision Support using ChatGPT. CoRR abs/2308.09731 (2023) - [i32]Daniele Malitesta, Claudio Pomo, Vito Walter Anelli, Alberto Carlo Maria Mancino, Eugenio Di Sciascio, Tommaso Di Noia:
A Topology-aware Analysis of Graph Collaborative Filtering. CoRR abs/2308.10778 (2023) - [i31]Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo, Tommaso Di Noia:
On Popularity Bias of Multimodal-aware Recommender Systems: a Modalities-driven Analysis. CoRR abs/2308.12911 (2023) - [i30]Dario Di Palma, Giovanni Maria Biancofiore, Vito Walter Anelli, Fedelucio Narducci, Tommaso Di Noia, Eugenio Di Sciascio:
Evaluating ChatGPT as a Recommender System: A Rigorous Approach. CoRR abs/2309.03613 (2023) - [i29]Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo, Felice Antonio Merra, Tommaso Di Noia, Eugenio Di Sciascio:
Formalizing Multimedia Recommendation through Multimodal Deep Learning. CoRR abs/2309.05273 (2023) - [i28]Daniele Malitesta, Claudio Pomo, Tommaso Di Noia:
Graph Neural Networks for Recommendation: Reproducibility, Graph Topology, and Node Representation. CoRR abs/2310.11270 (2023) - 2022
- [j49]Tommaso Di Noia, Nava Tintarev, Panagiota Fatourou, Markus Schedl:
Recommender systems under European AI regulations. Commun. ACM 65(4): 69-73 (2022) - [j48]Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
A Survey on Adversarial Recommender Systems: From Attack/Defense Strategies to Generative Adversarial Networks. ACM Comput. Surv. 54(2): 35:1-35:38 (2022) - [j47]Hossein A. Rahmani, Yashar Deldjoo, Tommaso Di Noia:
The role of context fusion on accuracy, beyond-accuracy, and fairness of point-of-interest recommendation systems. Expert Syst. Appl. 205: 117700 (2022) - [j46]Carmelo Ardito, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fatemeh Nazary:
Visual inspection of fault type and zone prediction in electrical grids using interpretable spectrogram-based CNN modeling. Expert Syst. Appl. 210: 118368 (2022) - [j45]Tommaso Di Noia, Francesco Maria Donini, Dietmar Jannach, Fedelucio Narducci, Claudio Pomo:
Conversational recommendation: Theoretical model and complexity analysis. Inf. Sci. 614: 325-347 (2022) - [j44]Silvana Bruno, Albina Scioti, Alessandra Pierucci, Rocco Rubino, Tommaso Di Noia, Fabio Fatiguso:
VERBUM - virtual enhanced reality for building modelling (virtual technical tour in digital twins for building conservation). J. Inf. Technol. Constr. 27: 20-47 (2022) - [j43]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara, Fedelucio Narducci:
User-controlled federated matrix factorization for recommender systems. J. Intell. Inf. Syst. 58(2): 287-309 (2022) - [j42]Rossella Tatoli, Luisa Lampignano, Ilaria Bortone, Rossella Donghia, Fabio Castellana, Roberta Zupo, Sarah Tirelli, Sara De Nucci, Annamaria Sila, Annalidia Natuzzi, Madia Lozupone, Chiara Griseta, Sabrina Sciarra, Simona Aresta, Giovanni De Pergola, Paolo Sorino, Domenico Lofù, Francesco Panza, Tommaso Di Noia, Rodolfo Sardone:
Dietary Patterns Associated with Diabetes in an Older Population from Southern Italy Using an Unsupervised Learning Approach. Sensors 22(6): 2193 (2022) - [j41]Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Azzurra Ragone, Joseph Trotta:
Semantic Interpretation of Top-N Recommendations. IEEE Trans. Knowl. Data Eng. 34(5): 2416-2428 (2022) - [c227]Vito Walter Anelli, Giovanni Maria Biancofiore, Alessandro De Bellis, Tommaso Di Noia, Eugenio Di Sciascio:
Interpretability of BERT Latent Space through Knowledge Graphs. CIKM 2022: 3806-3810 - [c226]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Daniele Malitesta, Claudio Pomo:
Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews. DL4SR@CIKM 2022 - [c225]Carmelo Ardito, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fatemeh Nazary:
IEEE13-AdvAttack A Novel Dataset for Benchmarking the Power of Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grid. CIKM 2022: 3817-3821 - [c224]Tommaso Di Noia, Francesco Maria Donini, Dietmar Jannach, Fedelucio Narducci, Claudio Pomo:
Towards a theoretical formalization of conversational recommendation. CIKM Workshops 2022 - [c223]Domenico Lofù, Andrea Pazienza, Carmelo Ardito, Tommaso Di Noia, Eugenio Di Sciascio, Felice Vitulano:
A Situation Awareness Computational Intelligent Model for Metabolic Syndrome Management. CogSIMA 2022: 118-124 - [c222]Domenico Lofù, Pietro Di Gennaro, Paolo Sorino, Tommaso Di Noia, Eugenio Di Sciascio:
CPU-side comparison for Key Agreement between Tree Parity Machines and standard Cryptographic Primitives. DESSERT 2022: 1-6 - [c221]Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta, Felice Antonio Merra:
Leveraging Content-Style Item Representation for Visual Recommendation. ECIR (2) 2022: 84-92 - [c220]Alberto Carlo Maria Mancino, Tommaso Di Noia:
Towards Differentially Private Machine Learning Models and Their Robustness to Adversaries. ICWE 2022: 455-461 - [c219]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo:
An Analysis of Local Explanation with LIME-RS. IIR 2022 - [c218]Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Alberto Carlo Maria Mancino:
Addressing Privacy in Recommender Systems with Federated Learning. IIR 2022 - [c217]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Daniele Malitesta, Claudio Pomo:
How Neighborhood Exploration influences Novelty and Diversity in Graph Collaborative Filtering. MORS@RecSys 2022 - [c216]Giovanni Maria Biancofiore, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci, Paolo Pastore:
Aspect based sentiment analysis in music: a case study with spotify. SAC 2022: 696-703 - [c215]Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Alberto Carlo Maria Mancino:
Inferring User Decision-Making Processes in Recommender Systems with Knowledge Graphs. SEBD 2022: 505-513 - [c214]Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco M. Donini, Eugenio Di Sciascio, Tommaso Di Noia:
The Challenging Reproducibility Task in Recommender Systems Research between Traditional and Deep Learning Models. SEBD 2022: 514-521 - [c213]Carmelo Ardito, Ilaria Bortone, Tommaso Colafiglio, Tommaso Di Noia, Eugenio Di Sciascio, Domenico Lofù, Fedelucio Narducci, Rodolfo Sardone, Paolo Sorino:
Brain Computer Interface: Deep Learning Approach to Predict Human Emotion Recognition. SMC 2022: 2689-2694 - [c212]Fabio Castellana, Simona Aresta, Paolo Sorino, Ilaria Bortone, Domenico Lofù, Fedelucio Narducci, Tommaso Di Noia, Eugenio Di Sciascio, Rodolfo Sardone:
An Artificial Neural Network Model to Assess Nutritional Factors Associated with Frailty in the Aging Population from Southern Italy. SMC 2022: 3228-3233 - [c211]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Dietmar Jannach, Claudio Pomo:
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art. UMAP 2022: 121-131 - [e14]Tommaso Di Noia, In-Young Ko, Markus Schedl, Carmelo Ardito:
Web Engineering - 22nd International Conference, ICWE 2022, Bari, Italy, July 5-8, 2022, Proceedings. Lecture Notes in Computer Science 13362, Springer 2022, ISBN 978-3-031-09916-8 [contents] - [r3]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
Adversarial Recommender Systems: Attack, Defense, and Advances. Recommender Systems Handbook 2022: 335-379 - [i27]Yashar Deldjoo, Fatemeh Nazary, Arnau Ramisa, Julian J. McAuley, Giovanni Pellegrini, Alejandro Bellogín, Tommaso Di Noia:
A Review of Modern Fashion Recommender Systems. CoRR abs/2202.02757 (2022) - [i26]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Dietmar Jannach, Claudio Pomo:
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art. CoRR abs/2203.01155 (2022) - [i25]Domenico Lofù, Pietro Tedeschi, Tommaso Di Noia, Eugenio Di Sciascio:
URANUS: Radio Frequency Tracking, Classification and Identification of Unmanned Aircraft Vehicles. CoRR abs/2207.06025 (2022) - [i24]Giovanni Maria Biancofiore, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci:
Interactive Question Answering Systems: Literature Review. CoRR abs/2209.01621 (2022) - 2021
- [j40]Yashar Deldjoo, Alejandro Bellogín, Tommaso Di Noia:
Explaining recommender systems fairness and accuracy through the lens of data characteristics. Inf. Process. Manag. 58(5): 102662 (2021) - [j39]Vito Walter Anelli, Pierpaolo Basile, Toine Bogers, Tommaso Di Noia, Francesco Maria Donini, Bamshad Mobasher, Cataldo Musto, Fedelucio Narducci, Casper Petersen, Maria Soledad Pera, Markus Zanker:
Report on the 3rd workshop of knowledge-aware and conversational recommender systems (KARS/ComplexRec) at RecSys 2021. SIGIR Forum 55(2): 17:1-17:9 (2021) - [j38]Yashar Deldjoo, Vito Walter Anelli, Hamed Zamani, Alejandro Bellogín, Tommaso Di Noia:
A flexible framework for evaluating user and item fairness in recommender systems. User Model. User Adapt. Interact. 31(3): 457-511 (2021) - [c210]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
A Formal Analysis of Recommendation Quality of Adversarially-trained Recommenders. CIKM 2021: 2852-2856 - [c209]Yashar Deldjoo, Tommaso Di Noia, Daniele Malitesta, Felice Antonio Merra:
A Study on the Relative Importance of Convolutional Neural Networks in Visually-Aware Recommender Systems. CVPR Workshops 2021: 3961-3967 - [c208]Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia, Antonio Ferrara, Fedelucio Narducci:
FedeRank: User Controlled Feedback with Federated Recommender Systems. ECIR (1) 2021: 32-47 - [c207]Vito Walter Anelli, Alejandro Bellogín, Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra:
MSAP: Multi-Step Adversarial Perturbations on Recommender Systems Embeddings. FLAIRS 2021 - [c206]Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara, Daniele Malitesta, Felice Antonio Merra, Claudio Pomo, Francesco Maria Donini, Eugenio Di Sciascio, Tommaso Di Noia:
How to Perform Reproducible Experiments in the ELLIOT Recommendation Framework: Data Processing, Model Selection, and Performance Evaluation. IIR 2021 - [c205]Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Alberto Carlo Maria Mancino:
Sparse Embeddings for Recommender Systems with Knowledge Graphs. IIR 2021 - [c204]Giovanni Maria Biancofiore, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci, Paolo Pastore:
GUapp: Enhancing Job Recommendations with Knowledge Graphs. IIR 2021 - [c203]Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Felice Antonio Merra:
A Regression Framework to Interpret the Robustness of Recommender Systems Against Shilling Attacks. IIR 2021 - [c202]Carmelo Ardito, Tommaso Di Noia, Eugenio Di Sciascio, Domenico Lofù, Andrea Pazienza, Felice Vitulano:
User Feedback to Improve the Performance of a Cyberattack Detection Artificial Intelligence System in the e-Health Domain. INTERACT (5) 2021: 295-299 - [c201]Carmelo Ardito, Tommaso Colafiglio, Tommaso Di Noia, Eugenio Di Sciascio:
A Biofeedback System to Compose Your Own Music While Dancing. INTERACT (5) 2021: 309-312 - [c200]Carmelo Ardito, Tommaso Colafiglio, Tommaso Di Noia, Eugenio Di Sciascio:
Brain Computer Interface, Visual Tracker and Artificial Intelligence for a Music Polyphony Generation System. INTERACT (5) 2021: 368-371 - [c199]Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Gaetano Pernisco, Vito Renò, Ettore Stella:
Towards Improving Car Point-Cloud Tracking Via Detection Updates. IPMV 2021: 30-34 - [c198]Carmelo Ardito, Tommaso Di Noia, Eugenio Di Sciascio, Domenico Lofù, Andrea Pazienza, Felice Vitulano:
An Artificial Intelligence Cyberattack Detection System to Improve Threat Reaction in e-Health. ITASEC 2021: 270-283 - [c197]Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia, Francesco Maria Donini, Vincenzo Paparella, Claudio Pomo:
Adherence and Constancy in LIME-RS Explanations for Recommendation (Long paper). KaRS/ComplexRec@RecSys 2021 - [c196]Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Daniele Malitesta, Felice Antonio Merra:
Adversarial Attacks against Visual Recommendation: an Investigation on the Influence of Items' Popularity. OHARS@RecSys 2021: 33-44 - [c195]Vito Walter Anelli, Tommaso Di Noia, Eugenio Di Sciascio, Antonio Ferrara, Alberto Carlo Maria Mancino:
Sparse Feature Factorization for Recommender Systems with Knowledge Graphs. RecSys 2021: 154-165 - [c194]