51 citations · 140 across the 9 of their papers we have counts for
19 papers
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia +2
Research on recommender systems algorithms, like other areas of applied machine learning, is largely dominated by efforts to improve the state-of-the-art, typically in terms of acc…
Adherence and Constancy in LIME-RS Explanations for Recommendation
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia +3
Explainable Recommendation has attracted a lot of attention due to a renewed interest in explainable artificial intelligence. In particular, post-hoc approaches have proved to be t…
The 2021 RecSys Challenge Dataset: Fairness is not optional
Luca Belli, Alykhan Tejani, Frank Portman +10
After the success the RecSys 2020 Challenge, we are describing a novel and bigger dataset that was released in conjunction with the ACM RecSys Challenge 2021. This year's dataset i…
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…
Understanding the Effects of Adversarial Personalized Ranking Optimization Method on Recommendation Quality
Vito Walter Anelli, Yashar Deldjoo, Tommaso Di Noia +1
Recommender systems (RSs) employ user-item feedback, e.g., ratings, to match customers to personalized lists of products. Approaches to top-k recommendation mainly rely on Learning…
Reenvisioning Collaborative Filtering vs Matrix Factorization
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia +1
Collaborative filtering models based on matrix factorization and learned similarities using Artificial Neural Networks (ANNs) have gained significant attention in recent years. Thi…