Cesare Bernardis

Orcid: 0000-0002-8972-0850

According to our database1, Cesare Bernardis authored at least 13 papers between 2018 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2022
On the effectiveness of neighborhood-based models in recommender systems
PhD thesis, 2022

NFC: a deep and hybrid item-based model for item cold-start recommendation.
User Model. User Adapt. Interact., 2022

Analyzing and improving stability of matrix factorization for recommender systems.
J. Intell. Inf. Syst., 2022

Multi-stage Ensemble Model for Cross-market Recommendation.
CoRR, 2022

From Data Analysis to Intent-Based Recommendation: An Industrial Case Study in the Video Domain.
IEEE Access, 2022

On the impact of data sampling on hyper-parameter optimisation of recommendation algorithms.
Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

2021
On the instability of embeddings for recommender systems: the case of matrix factorization.
Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021

Lightweight and Scalable Model for Tweet Engagements Predictions in a Resource-constrained Environment.
Proceedings of the RecSys Challenge 2021: Proceedings of the Recommender Systems Challenge 2021, 2021

Eigenvalue Perturbation for Item-based Recommender Systems.
Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

2020
Multi-Objective Blended Ensemble For Highly Imbalanced Sequence Aware Tweet Engagement Prediction.
Proceedings of the RecSys Challenge '20: Proceedings of the Recommender Systems Challenge 2020, 2020

2019
Estimating Confidence of Individual User Predictions in Item-based Recommender Systems.
Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization, 2019

Leveraging laziness, browsing-pattern aware stacked models for sequential accommodation learning to rank.
Proceedings of the Workshop on ACM Recommender Systems Challenge, 2019

2018
A novel graph-based model for hybrid recommendations in cold-start scenarios.
CoRR, 2018


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