Daniele Malitesta
Orcid: 0000-0003-2228-0333
According to our database1,
Daniele Malitesta
authored at least 40 papers
between 2020 and 2024.
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Bibliography
2024
SIGIR Forum, June, 2024
Report on the 1st International Workshop on Graph-Based Approaches in Information Retrieval (IRonGraphs 2024) at ECIR 2024.
SIGIR Forum, June, 2024
CoRR, 2024
Dot Product is All You Need: Bridging the Gap Between Item Recommendation and Link Prediction.
CoRR, 2024
Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach.
CoRR, 2024
Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024
A Novel Evaluation Perspective on GNNs-based Recommender Systems through the Topology of the User-Item Graph.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024
KGUF: Simple Knowledge-Aware Graph-Based Recommender with User-Based Semantic Features Filtering.
Proceedings of the Advances on Graph-Based Approaches in Information Retrieval, 2024
First International Workshop on Graph-Based Approaches in Information Retrieval (IRonGraphs 2024).
Proceedings of the Advances in Information Retrieval, 2024
Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation?
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
2023
Graph Neural Networks for Recommendation: Reproducibility, Graph Topology, and Node Representation.
CoRR, 2023
An Out-of-the-Box Application for Reproducible Graph Collaborative Filtering extending the Elliot Framework.
Proceedings of the Adjunct Proceedings of the 31st ACM Conference on User Modeling, 2023
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023
Proceedings of the 17th ACM Conference on Recommender Systems, 2023
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023
On Popularity Bias of Multimodal-aware Recommender Systems: A Modalities-driven Analysis.
Proceedings of the 1st International Workshop on Deep Multimodal Learning for Information Retrieval, 2023
Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation.
Proceedings of the 31st ACM International Conference on Multimedia, 2023
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), 2023
Examining Fairness in Graph-Based Collaborative Filtering: A Consumer and Producer Perspective.
Proceedings of the 13th Italian Information Retrieval Workshop (IIR 2023), 2023
Proceedings of the Advances in Information Retrieval, 2023
2022
The Challenging Reproducibility Task in Recommender Systems Research between Traditional and Deep Learning Models.
Proceedings of the 30th Italian Symposium on Advanced Database Systems, 2022
How Neighborhood Exploration influences Novelty and Diversity in Graph Collaborative Filtering.
Proceedings of the 2nd Workshop on Multi-Objective Recommender Systems co-located with 16th ACM Conference on Recommender Systems (RecSys 2022), 2022
Proceedings of the Advances in Information Retrieval, 2022
Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews.
Proceedings of the Workshop on Deep Learning for Search and Recommendation (DL4SR 2022) co-located with the 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), 2022
2021
A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021
Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021
Adversarial Attacks against Visual Recommendation: an Investigation on the Influence of Items' Popularity.
Proceedings of the Second Workshop on Online Misinformation- and Harm-Aware Recommender Systems co-located with 15th ACM Conference on Recommender Systems (RecSys 2021), 2021
Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021
How to Perform Reproducible Experiments in the ELLIOT Recommendation Framework: Data Processing, Model Selection, and Performance Evaluation.
Proceedings of the 11th Italian Information Retrieval Workshop 2021, 2021
A Study on the Relative Importance of Convolutional Neural Networks in Visually-Aware Recommender Systems.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021
2020
An Empirical Study of DNNs Robustification Inefficacy in Protecting Visual Recommenders.
CoRR, 2020
Proceedings of the 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2020
Proceedings of the 50th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops, 2020
Assessing Perceptual and Recommendation Mutation of Adversarially-Poisoned Visual Recommenders (short paper).
Proceedings of the AIxIA 2020 Discussion Papers Workshop co-located with the the 19th International Conference of the Italian Association for Artificial Intelligence (AIxIA2020), 2020