16 citations · 29 across the 7 of their papers we have counts for
4 papers · 1 filter
Demystifying Sequential Recommendations: Counterfactual Explanations via Genetic Algorithms
Domiziano Scarcelli, Filippo Betello, Giuseppe Perelli +2
Sequential Recommender Systems (SRSs) have demonstrated remarkable effectiveness in capturing users' evolving preferences. However, their inherent complexity as "black box" models…
The Role of Fake Users in Sequential Recommender Systems
Filippo Betello
Sequential Recommender Systems (SRSs) are widely used to model user behavior over time, yet their robustness remains an under-explored area of research. In this paper, we conduct a…
A Reproducible Analysis of Sequential Recommender Systems
Filippo Betello, Antonio Purificato, Federico Siciliano +4
Sequential Recommender Systems (SRSs) have emerged as a highly efficient approach to recommendation systems. By leveraging sequential data, SRSs can identify temporal patterns in u…
Investigating the Robustness of Sequential Recommender Systems Against Training Data Perturbations
Filippo Betello, Federico Siciliano, Pushkar Mishra +1
Sequential Recommender Systems (SRSs) are widely employed to model user behavior over time. However, their robustness in the face of perturbations in training data remains a largel…