Massimo Quadrana

According to our database, Massimo Quadrana authored at least 31 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

MuRS: Music Recommender Systems Workshop.

Andres Ferraro, Peter Knees, Massimo Quadrana, Tao Ye, Fabien Gouyon

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

2022

Session-Based Recommender Systems.

Dietmar Jannach, Massimo Quadrana, Paolo Cremonesi

Proceedings of the Recommender Systems Handbook, 2022

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

Cesare Bernardis, Maurizio Ferrari Dacrema, Fernando Benjamín Pérez Maurera, Massimo Quadrana, Mario Scriminaci, Paolo Cremonesi

IEEE Access, 2022

Multi-objective Hyper-parameter Optimization of Behavioral Song Embeddings.

Massimo Quadrana, Antoine Larreche-Mouly, Matthias Mauch

Proceedings of the 23rd International Society for Music Information Retrieval Conference, 2022

2021

Bootstrapping a Music Voice Assistant with Weak Supervision.

Sergio Oramas, Massimo Quadrana, Fabien Gouyon

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Papers, 2021

2020

Maximizing the Engagement: Exploring New Signals of Implicit Feedback in Music Recommendations.

Andres Ferraro, Sergio Oramas, Massimo Quadrana, Xavier Serra

Proceedings of the Workshops on Recommendation in Complex Scenarios and the Impact of Recommender Systems co-located with 14th ACM Conference on Recommender Systems (RecSys 2020), 2020

2019

Order, context and popularity bias in next-song recommendations.

Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer

Int. J. Multim. Inf. Retr., 2019

Tutorial: Sequence-Aware Recommender Systems.

Massimo Quadrana, Dietmar Jannach, Paolo Cremonesi

Proceedings of the Companion of The 2019 World Wide Web Conference, 2019

2018

Using visual features based on MPEG-7 and deep learning for movie recommendation.

Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi

Int. J. Multim. Inf. Retr., 2018

Sequence-Aware Recommender Systems.

Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach

ACM Comput. Surv., 2018

The Importance of Song Context and Song Order in Automated Music Playlist Generation.

Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer

CoRR, 2018

Modeling Musical Taste Evolution with Recurrent Neural Networks.

Massimo Quadrana, Marta Reznáková, Tao Ye, Erik Schmidt, Hossein Vahabi

CoRR, 2018

Sequence-aware recommendation.

Massimo Quadrana, Paolo Cremonesi

Proceedings of the 12th ACM Conference on Recommender Systems, 2018

2017

Algorithms for Sequence-Aware Recommender Systems.

Massimo Quadrana

PhD thesis, 2017

Toward Active Learning in Cross-domain Recommender Systems.

Roberto Pagano, Massimo Quadrana, Mehdi Elahi, Paolo Cremonesi

CoRR, 2017

Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation.

Yashar Deldjoo, Massimo Quadrana, Mehdi Elahi, Paolo Cremonesi

CoRR, 2017

Deriving Item Features Relevance from Past User Interactions.

Leonardo Cella, Stefano Cereda, Massimo Quadrana, Paolo Cremonesi

Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, 2017

The Importance of Song Context in Music Playlists.

Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer, Paolo Cremonesi

Proceedings of the Poster Track of the 11th ACM Conference on Recommender Systems (RecSys 2017), 2017

Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks.

Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi

Proceedings of the Eleventh ACM Conference on Recommender Systems, 2017

The effect of different video summarization models on the quality of video recommendation based on low-level visual features.

Yashar Deldjoo, Paolo Cremonesi, Markus Schedl, Massimo Quadrana

Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing, 2017

2016

Content-Based Video Recommendation System Based on Stylistic Visual Features.

Yashar Deldjoo, Mehdi Elahi, Paolo Cremonesi, Franca Garzotto, Pietro Piazzolla, Massimo Quadrana

J. Data Semant., 2016

The Contextual Turn: from Context-Aware to Context-Driven Recommender Systems.

Roberto Pagano, Paolo Cremonesi, Martha A. Larson, Balázs Hidasi, Domonkos Tikk, Alexandros Karatzoglou, Massimo Quadrana

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations.

Balázs Hidasi, Massimo Quadrana, Alexandros Karatzoglou, Domonkos Tikk

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

Multi-stack ensemble for job recommendation.

Tommaso Carpi, Marco Edemanti, Ervin Kamberoski, Elena Sacchi, Paolo Cremonesi, Roberto Pagano, Massimo Quadrana

Proceedings of the 2016 Recommender Systems Challenge, 2016

2015

An efficient closed frequent itemset miner for the MOA stream mining system.

Massimo Quadrana, Albert Bifet, Ricard Gavaldà

AI Commun., 2015

30Music Listening and Playlists Dataset.

Roberto Turrin, Massimo Quadrana, Andrea Condorelli, Roberto Pagano, Paolo Cremonesi

Proceedings of the Poster Proceedings of the 9th ACM Conference on Recommender Systems, 2015

Toward Building a Content-Based Video Recommendation System Based on Low-Level Features.

Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi

Proceedings of the E-Commerce and Web Technologies, 2015

Toward Effective Movie Recommendations Based on Mise-en-Scène Film Styles.

Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi, Franca Garzotto

Proceedings of the 11th Biannual Conference on Italian SIGCHI Chapter, 2015

2014

Recommending without short head.

Paolo Cremonesi, Franca Garzotto, Roberto Pagano, Massimo Quadrana

Proceedings of the 23rd International World Wide Web Conference, 2014

Cross-domain recommendations without overlapping data: myth or reality?

Paolo Cremonesi, Massimo Quadrana

Proceedings of the Eighth ACM Conference on Recommender Systems, 2014

2013

Evaluating top-n recommendations "when the best are gone".

Paolo Cremonesi, Franca Garzotto, Massimo Quadrana

Proceedings of the Seventh ACM Conference on Recommender Systems, 2013