Massimo Quadrana - Citegraph

Author Info

Name	Affiliation	Papers
MASSIMO QUADRANA	Politecnico di Milano, Milan, Italy	26
Collaborators	Citations	PageRank
38	239	13.89
Referers	Referees	References
623	701	325

Search Limit

100701

Publications (26 rows)

Collaborators (38 rows)

Referers (100 rows)

Referees (100 rows)

Title	Citations	PageRank	Year
From Data Analysis to Intent-Based Recommendation: An Industrial Case Study in the Video Domain	0	0.34	2022
Bootstrapping a Music Voice Assistant with Weak Supervision.	0	0.34	2021
Maximizing the Engagement - Exploring New Signals of Implicit Feedback in Music Recommendations.	0	0.34	2020
Tutorial: Sequence-Aware Recommender Systems	0	0.34	2019
Order, context and popularity bias in next-song recommendations	2	0.39	2019
Sequence-Aware Recommender Systems.	23	0.88	2018
The Importance of Song Context and Song Order in Automated Music Playlist Generation.	0	0.34	2018
Modeling Musical Taste Evolution with Recurrent Neural Networks.	0	0.34	2018
Sequence-aware recommendation.	0	0.34	2018
Using visual features based on MPEG-7 and deep learning for movie recommendation.	7	0.41	2018
Deriving Item Features Relevance from Past User Interactions.	3	0.38	2017
The Importance of Song Context in Music Playlists.	5	0.42	2017
Toward Active Learning in Cross-domain Recommender Systems.	1	0.35	2017
Using Mise-En-Scène Visual Features based on MPEG-7 and Deep Learning for Movie Recommendation.	1	0.34	2017
Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks.	52	1.25	2017
Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations.	67	1.74	2016
The Contextual Turn: from Context-Aware to Context-Driven Recommender Systems.	4	0.46	2016
Multi-stack ensemble for job recommendation.	0	0.34	2016
Content-Based Video Recommendation System Based on Stylistic Visual Features.	34	0.99	2016
Toward Effective Movie Recommendations Based on Mise-en-Scène Film Styles	5	0.42	2015
30Music Listening and Playlists Dataset.	13	1.01	2015
Toward Building a Content-Based Video Recommendation System Based on Low-Level Features.	6	0.45	2015
Cross-domain recommendations without overlapping data: myth or reality?	7	0.45	2014
Recommending without short head	2	0.40	2014
Evaluating top-n recommendations "when the best are gone"	2	0.39	2013
An efficient closed frequent itemset miner for the MOA stream mining system	5	0.44	2013