Maurizio Ferrari Dacrema
Maurizio Ferrari Dacrema
PhD Student, DEIB, Politecnico di Milano
Email verificata su polimi.it - Home page
TitoloCitata daAnno
Movie Genome: Alleviating New Item Cold Start in Movie Recommendation
Y Deldjoo, M Ferrari Dacrema, M Gabriel Constantin, H Eghbal-Zadeh, ...
User Modeling and User-Adapted Interaction (UMUAI), 2019
62019
Artist-driven layering and user's behaviour impact on recommendations in a playlist continuation scenario
S Antenucci, S Boglio, E Chioso, E Dervishaj, S Kang, T Scarlatti, ...
Proceedings of the ACM Recommender Systems Challenge 2018, 4, 2018
52018
Deriving item features relevance from collaborative domain knowledge
M Ferrari Dacrema, A Gasparin, P Cremonesi
Proceedings of KaRS 2018 Workshop on Knowledge-aware and Conversational …, 2018
12018
Eigenvalue analogy for confidence estimation in item-based recommender systems
M Ferrari Dacrema, P Cremonesi
Proceedings of the Late-Breaking Results track part of the Twelfth ACM …, 2018
1*2018
A novel graph-based model for hybrid recommendations in cold-start scenarios
C Bernardis, M Ferrari Dacrema, P Cremonesi
Proceedings of the Late-Breaking Results track part of the Twelfth ACM …, 2018
12018
A novel graph-based model for hybrid recommendations in cold-start scenarios
C BERNARDIS
Italy, 2018
12018
User Preference Sources: Explicit vs. Implicit Feedback
P Cremonesi, F Garzotto, M Ferrari Dacrema
Collaborative Recommendations, 233-252, 2018
12018
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches
M Ferrari Dacrema, P Cremonesi, D Jannach
Proceedings of the 13th ACM Conference on Recommender Systems (RecSys 2019), 2019
2019
Estimating Confidence of Individual User Predictions in Item-based Recommender Systems
C Bernardis, M Ferrari Dacrema, P Cremonesi
Proceedings of the 27th ACM Conference on User Modeling, Adaptation and …, 2019
2019
Rating aware feature selection in content-based recommender systems
A Cano
Italy, 2019
2019
Eigenvalues as confidence estimators in item based recommender systems
S ANTENUCCI, E CHIOSO
Italy, 2019
2019
Automated feature engineering for recommender systems
I INAJJAR, G LOCCI
Italy, 2018
2018
Aggregating Models for Anomaly Detection in Space Systems: Results from the FCTMAS Study
F Amigoni, M Ferrari Dacrema, A Donati, C Laroque, M Lavagna, A Riva
International Conference on Intelligent Autonomous Systems, 142-160, 2018
2018
A feature-based machine learning approach for the cold start item problem
M BIANCHI, A GASPARIN
Italy, 2017
2017
Bayesian optimization for ensemble hyperparameters in job recommendation
F CESARO, M DAGRADA
Italy, 2017
2017
Un metodo di ricerca della struttura ottima di un sistema multiagente per l’individuazione di anomalie in applicazioni spaziali
M FERRARI DACREMA
Italy, 2016
2016
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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