Name
Affiliation
Papers
PAOLO CREMONESI
Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milan, Italy
149
Collaborators
Citations 
PageRank 
186
1306
87.23
Referers 
Referees 
References 
2614
2706
1757
Search Limit
1001000
Title
Citations
PageRank
Year
Preface to the special issue on dynamic recommender systems and user models00.342022
From Data Analysis to Intent-Based Recommendation: An Industrial Case Study in the Video Domain00.342022
Analyzing and improving stability of matrix factorization for recommender systems00.342022
Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers00.342022
Offline Evaluation of Recommender Systems in a User Interface With Multiple Carousels00.342022
Towards Recommender Systems with Community Detection and Quantum Computing00.342022
NFC: a deep and hybrid item-based model for item cold-start recommendation10.392022
Measuring the Ranking Quality of Recommendations in a Two-Dimensional Carousel Setting.00.342021
Optimizing the Selection of Recommendation Carousels with Quantum Computing00.342021
A Methodology for the Offline Evaluation of Recommender Systems in a User Interface with Multiple Carousels10.352021
CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions.00.342021
On the instability of embeddings for recommender systems: the case of matrix factorization00.342021
Eigenvalue Perturbation for Item-based Recommender Systems00.342021
Methodological Issues in Recommender Systems Research (Extended Abstract).00.342020
Recommender Systems Leveraging Multimedia Content90.522020
Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features.00.342019
A Virtual Teaching Assistant for Personalized Learning.00.342019
Tutorial: Sequence-Aware Recommender Systems00.342019
A pragmatic and industry-aware approach toward the design of on-line recommender systems.00.342019
Are we really making much progress? A worrying analysis of recent neural recommendation approaches330.872019
A novel graph-based model for hybrid recommendations in cold-start scenarios.10.342018
Sequence-Aware Recommender Systems.230.882018
Deriving item features relevance from collaborative domain knowledge.10.342018
Audio-visual encoding of multimedia content for enhancing movie recommendations.50.422018
Eigenvalue analogy for confidence estimation in item-based recommender systems.00.342018
Sequence-aware recommendation.00.342018
Deriving Item Features Relevance from Past User Interactions.30.382017
The Importance of Song Context in Music Playlists.50.422017
Kernalized Collaborative Contextual Bandits.00.342017
Toward Active Learning in Cross-domain Recommender Systems.10.352017
Exploring the Semantic Gap for Movie Recommendations120.492017
Estimate Features Relevance for Groups of Users.00.342017
Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation.10.342017
The Contextual Turn: from Context-Aware to Context-Driven Recommender Systems.40.462016
Multi-stack ensemble for job recommendation.00.342016
Explicit Elimination of Similarity Blocking for Session-based Recommendation.10.362016
Content-Based Video Recommendation System Based on Stylistic Visual Features.340.992016
Compact Markov-modulated models for multiclass trace fitting.10.352016
Dynamic and Interactive Lighting for Fashion Store Windows.10.352016
Using Visual Features and Latent Factors for Movie Recommendation20.362016
Sparse vs. Non-sparse: Which One Is Better for Practical Visual Tracking?00.342016
Bridging Physical Space and Digital Landscape to Drive Retail Innovation.00.342016
Towards a smart retail environment30.462015
Decision Making through Polarized Summarization of User Reviews.00.342015
Toward Effective Movie Recommendations Based on Mise-en-Scène Film Styles50.422015
Personalized and Context-Aware TV Program Recommendations Based on Implicit Feedback.10.352015
30Music Listening and Playlists Dataset.131.012015
Investigating the Decision Making Process of Users based on the PoliMovie Dataset.00.342015
Interaction Design Patterns in Recommender Systems20.362015
Making Fashion More Trendy through Touchless Interactive Displays Integrated with Mobile Devices00.342015
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