Massimo Quadrana

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 30

Top Topics

Movie Recommendation

Closed Itemsets

Recommender Systems

Top Venues

Int. J. Multim. Inf. Retr.

Publications

Andres Ferraro, Peter Knees, Massimo Quadrana, Tao Ye, Fabien Gouyon
MuRS: Music Recommender Systems Workshop. RecSys (2023)
Massimo Quadrana, Antoine Larreche-Mouly, Matthias Mauch
Multi-objective Hyper-parameter Optimization of Behavioral Song Embeddings. ISMIR (2022)
Massimo Quadrana, Antoine Larreche-Mouly, Matthias Mauch
Multi-objective Hyper-parameter Optimization of Behavioral Song Embeddings. CoRR (2022)
Cesare Bernardis, Maurizio Ferrari Dacrema, Fernando Benjamín Pérez Maurera, Massimo Quadrana, Mario Scriminaci, Paolo Cremonesi
From Data Analysis to Intent-Based Recommendation: An Industrial Case Study in the Video Domain. IEEE Access 10 (2022)
Sergio Oramas, Massimo Quadrana, Fabien Gouyon
Bootstrapping a Music Voice Assistant with Weak Supervision. NAACL-HLT (Industry Papers) (2021)
Andres Ferraro, Sergio Oramas, Massimo Quadrana, Xavier Serra
Maximizing the Engagement: Exploring New Signals of Implicit Feedback in Music Recommendations. ComplexRec-ImpactRS@RecSys (2020)
Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer
Order, context and popularity bias in next-song recommendations. Int. J. Multim. Inf. Retr. 8 (2) (2019)
Massimo Quadrana, Dietmar Jannach, Paolo Cremonesi
Tutorial: Sequence-Aware Recommender Systems. WWW (Companion Volume) (2019)
Massimo Quadrana, Paolo Cremonesi
Sequence-aware recommendation. RecSys (2018)
Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach
Sequence-aware Recommender Systems. UMAP (2018)
Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer
The Importance of Song Context and Song Order in Automated Music Playlist Generation. CoRR (2018)
Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach
Sequence-Aware Recommender Systems. ACM Comput. Surv. 51 (4) (2018)
Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi
Using visual features based on MPEG-7 and deep learning for movie recommendation. Int. J. Multim. Inf. Retr. 7 (4) (2018)
Massimo Quadrana, Marta Reznáková, Tao Ye, Erik Schmidt, Hossein Vahabi
Modeling Musical Taste Evolution with Recurrent Neural Networks. CoRR (2018)
Massimo Quadrana, Paolo Cremonesi, Dietmar Jannach
Sequence-Aware Recommender Systems. CoRR (2018)
Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer, Paolo Cremonesi
The Importance of Song Context in Music Playlists. RecSys Posters (2017)
Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi
Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks. RecSys (2017)
Massimo Quadrana, Alexandros Karatzoglou, Balázs Hidasi, Paolo Cremonesi
Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks. CoRR (2017)
Yashar Deldjoo, Paolo Cremonesi, Markus Schedl, Massimo Quadrana
The effect of different video summarization models on the quality of video recommendation based on low-level visual features. CBMI (2017)
Roberto Pagano, Massimo Quadrana, Mehdi Elahi, Paolo Cremonesi
Toward Active Learning in Cross-domain Recommender Systems. CoRR (2017)
Leonardo Cella, Stefano Cereda, Massimo Quadrana, Paolo Cremonesi
Deriving Item Features Relevance from Past User Interactions. UMAP (2017)
Yashar Deldjoo, Massimo Quadrana, Mehdi Elahi, Paolo Cremonesi
Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation. CoRR (2017)
Roberto Pagano, Paolo Cremonesi, Martha A. Larson, Balázs Hidasi, Domonkos Tikk, Alexandros Karatzoglou, Massimo Quadrana
The Contextual Turn: from Context-Aware to Context-Driven Recommender Systems. RecSys (2016)
Yashar Deldjoo, Mehdi Elahi, Paolo Cremonesi, Franca Garzotto, Pietro Piazzolla, Massimo Quadrana
Content-Based Video Recommendation System Based on Stylistic Visual Features. J. Data Semant. 5 (2) (2016)
Tommaso Carpi, Marco Edemanti, Ervin Kamberoski, Elena Sacchi, Paolo Cremonesi, Roberto Pagano, Massimo Quadrana
Multi-stack ensemble for job recommendation. RecSys Challenge (2016)
Balázs Hidasi, Massimo Quadrana, Alexandros Karatzoglou, Domonkos Tikk
Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations. RecSys (2016)
Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi
Toward Building a Content-Based Video Recommendation System Based on Low-Level Features. EC-Web (2015)
Roberto Turrin, Massimo Quadrana, Andrea Condorelli, Roberto Pagano, Paolo Cremonesi
30Music Listening and Playlists Dataset. RecSys Posters (2015)
Yashar Deldjoo, Mehdi Elahi, Massimo Quadrana, Paolo Cremonesi, Franca Garzotto
Toward Effective Movie Recommendations Based on Mise-en-Scène Film Styles. CHItaly (2015)
Massimo Quadrana, Albert Bifet, Ricard Gavaldà
An efficient closed frequent itemset miner for the MOA stream mining system. AI Commun. 28 (1) (2015)
Paolo Cremonesi, Massimo Quadrana
Cross-domain recommendations without overlapping data: myth or reality? RecSys (2014)
Paolo Cremonesi, Franca Garzotto, Roberto Pagano, Massimo Quadrana
Recommending without short head. WWW (Companion Volume) (2014)
Paolo Cremonesi, Franca Garzotto, Massimo Quadrana
Evaluating top-n recommendations "when the best are gone". RecSys (2013)
Massimo Quadrana, Albert Bifet, Ricard Gavaldà
An Efficient Closed Frequent Itemset Miner for the Moa Stream Mining System. CCIA (2013)