- Aaron Ng, Rishabh Mehrotra:
Investigating the Impact of Audio States & Transitions for Track Sequencing in Music Streaming Sessions. RecSys 2020: 697-702 - Gustavo Penha, Claudia Hauff:
What does BERT know about books, movies and music? Probing BERT for Conversational Recommendation. RecSys 2020: 388-397 - Dougal Shakespeare, Lorenzo Porcaro, Emilia Gómez, Carlos Castillo:
Exploring Artist Gender Bias in Music Recommendation. ComplexRec-ImpactRS@RecSys 2020 - 2019
- Andres Ferraro:
Music cold-start and long-tail recommendation: bias in deep representations. RecSys 2019: 586-590 - Sophia Hadash, Yu Liang, Martijn C. Willemsen:
How Playlist Evaluation Compares to Track Evaluations in Music Recommender Systems. IntRS@RecSys 2019: 1-9 - Sandy Manolios, Alan Hanjalic, Cynthia C. S. Liem:
The influence of personal values on music taste: towards value-based music recommendations. RecSys 2019: 501-505 - Bruno L. Pereira, Alberto Ueda, Gustavo Penha, Rodrygo L. T. Santos, Nivio Ziviani:
Online learning to rank for sequential music recommendation. RecSys 2019: 237-245 - Timothy Schmeier, Joseph Chisari, Sam Garrett, Brett Vintch:
Music recommendations in hyperbolic space: an application of empirical bayes and hierarchical poincaré embeddings. RecSys 2019: 437-441 - 2018
- Ching-Wei Chen, Paul Lamere, Markus Schedl, Hamed Zamani:
Recsys challenge 2018: automatic music playlist continuation. RecSys 2018: 527-528 - Yucheng Jin, Nava Tintarev, Katrien Verbert:
Effects of personal characteristics on music recommender systems with different levels of controllability. RecSys 2018: 13-21 - Jaehun Kim, Minz Won, Cynthia C. S. Liem, Alan Hanjalic:
Towards Seed-Free Music Playlist Generation: Enhancing Collaborative Filtering with Playlist Title Information. RecSys Challenge 2018: 14:1-14:6 - Vikas Kumar, Sabirat Rubya, Joseph A. Konstan, Loren Terveen:
Risk "Attention" or "Adventure": A Qualitative Study of Novelty and Familiarity in Music Listening. IntRS@RecSys 2018: 15-23 - Feng Lu, Nava Tintarev:
A Diversity Adjusting Strategy with Personality for Music Recommendation. IntRS@RecSys 2018: 7-14 - Malte Ludewig, Iman Kamehkhosh, Nick Landia, Dietmar Jannach:
Effective Nearest-Neighbor Music Recommendations. RecSys Challenge 2018: 3:1-3:6 - Noveen Sachdeva, Kartik Gupta, Vikram Pudi:
Attentive neural architecture incorporating song features for music recommendation. RecSys 2018: 417-421 - Lin Zhu, Bowen He, Mengxin Ji, Cheng Ju, Yihong Chen:
Automatic Music Playlist Continuation via Neighbor-based Collaborative Filtering and Discriminative Reweighting/Reranking. RecSys Challenge 2018: 10:1-10:6 - 2017
- Himan Abdollahpouri, Steve Essinger:
Towards Effective Exploration/Exploitation in Sequential Music Recommendation. RecSys Posters 2017 - Bruce Ferwerda, Marko Tkalcic, Markus Schedl:
Personality Traits and Music Genre Preferences: How Music Taste Varies Over Age Groups. RecTemp@RecSys 2017: 16-20 - Byungsoo Jeon, Chanju Kim, Adrian Kim, Dongwon Kim, Jangyeon Park, JungWoo Ha:
Music Emotion Recognition via End-to-End Multimodal Neural Networks. RecSys Posters 2017 - Sergio Oramas, Oriol Nieto, Mohamed Sordo, Xavier Serra:
A Deep Multimodal Approach for Cold-start Music Recommendation. DLRS@RecSys 2017: 32-37 - Markus Schedl, Peter Knees, Fabien Gouyon:
New Paths in Music Recommender Systems Research. RecSys 2017: 392-393 - Andreu Vall, Hamid Eghbal-zadeh, Matthias Dorfer, Markus Schedl, Gerhard Widmer:
Music Playlist Continuation by Learning from Hand-Curated Examples and Song Features: Alleviating the Cold-Start Problem for Rare and Out-of-Set Songs. DLRS@RecSys 2017: 46-54 - Andreu Vall, Massimo Quadrana, Markus Schedl, Gerhard Widmer, Paolo Cremonesi:
The Importance of Song Context in Music Playlists. RecSys Posters 2017 - 2016
- Òscar Celma:
The Exploit-Explore Dilemma in Music Recommendation. RecSys 2016: 377 - Chih-Ming Chen, Ming-Feng Tsai, Yu-Ching Lin, Yi-Hsuan Yang:
Query-based Music Recommendations via Preference Embedding. RecSys 2016: 79-82 - Chih-Ming Chen, Chun-Yao Yang, Chih-Chun Hsia, Yian Chen, Ming-Feng Tsai:
Music Playlist Recommendation via Preference Embedding. RecSys Posters 2016 - Sander Dieleman:
Keynote: Deep learning for audio-based music recommendation. DLRS@RecSys 2016: 1 - Kurt Jacobson, Vidhya Murali, Edward Newett, Brian Whitman, Romain Yon:
Music Personalization at Spotify. RecSys 2016: 373 - Melissa Onori, Alessandro Micarelli, Giuseppe Sansonetti:
A Comparative Analysis of Personality-Based Music Recommender Systems. EMPIRE@RecSys 2016: 55-59 - 2015
- Chih-Ming Chen, Po-Chuan Chien, Yu-Ching Lin, Ming-Feng Tsai, Yi-Hsuan Yang:
Do You Have a Pop Face? Here is a Pop Song. Using Profile Pictures to Mitigate the Cold-start Problem in Music Recommender Systems. RecSys Posters 2015