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Combining usage and content in an online music recommendation system for music in the long-tail

Marcos Aurélio Domingues, Fabien Gouyon, Alípio Mário Jorge, José Paulo Leal, João Vinagre, Luís Lemos, Mohamed Sordo
2012 Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion  
We describe an online evaluation experiment performed in real time on a commercial music web site, specialised in content from the very long tail of music content.  ...  In this paper we propose a hybrid music recommender system, which combines usage and content data.  ...  There, the system Mix presents a gain of 16% when compared to Usage. CONCLUSIONS In this paper we proposed a music recommender system that combines usage and content data.  ... 
doi:10.1145/2187980.2188224 dblp:conf/www/DominguesGJLVLS12 fatcat:3tsxfe2oyzbqfdplm4vvfankcy

Combining usage and content in an online recommendation system for music in the Long Tail

Marcos Aurélio Domingues, Fabien Gouyon, Alípio Mário Jorge, José Paulo Leal, João Vinagre, Luís Lemos, Mohamed Sordo
2012 International Journal of Multimedia Information Retrieval  
We describe an online evaluation experiment performed in real time on a commercial web site, specialized in content from the very long tail of music content.  ...  In this paper we propose a hybrid music recommender system, which combines usage and content data.  ...  Summary In this paper we have proposed and evaluated a music recommender system that combines usage and content data.  ... 
doi:10.1007/s13735-012-0025-1 fatcat:g7fb7sypaba4tpp6vabnel7ad4

Hybrid music information retrieval

Peter Knees, Markus Schedl, Òscar Celma
2013 International Journal of Multimedia Information Retrieval  
This also calls for novel methods for user-centric evaluation of music retrieval systems.  ...  Given the strengths and shortcomings inherent to both content-based and context-based approaches, hybrid methods that intelligently combine the two are essential. Such P. Knees (B) · M. Schedl  ...  Combining Usage and Content in an Online Recommendation System for Music in the Long-Tail  ... 
doi:10.1007/s13735-013-0033-9 fatcat:bklygnizmjcytcwqumybifkq74

If You Like Radiohead, You Might Like This Article

Oscar Celma, Paul Lamere
2011 The AI Magazine  
In this article we explore one such tool: music recommendation.  ...  We describe common music recommendation use cases such as finding new artists, finding others with similar listening taste, and generating interesting music playlists.  ...  The authors would like to specially thank Keith Emerson and Timothy John Taylor for providing inspiration and encouragement to continue pursuing this subject area. Notes 1.  ... 
doi:10.1609/aimag.v32i3.2363 fatcat:wpnq6gltebch5leyee4rvhqpga

Exploring acoustic similarity for novel music recommendation

Derek S Cheng, Thorsten Joachims, Douglas Turnbull
2020 Zenodo  
Secondly, is acoustic similarity a good proxy for how an individual might construct a playlist or recommend music to a friend?  ...  Most commercial music services rely on collaborative filtering to recommend artists and songs.  ...  An alternative to CF systems are content-based (CB) recommender systems that make use of the audio signal for recommendation.  ... 
doi:10.5281/zenodo.4245500 fatcat:ds4234rfzngarexpylpvynonjm

Sound and Music Recommendation with Knowledge Graphs

Sergio Oramas, Vito Claudio Ostuni, Tommaso Di Noia, Xavier Serra, Eugenio Di Sciascio
2016 ACM Transactions on Intelligent Systems and Technology  
In addition, we show how the semantic expansion of the initial descriptions helps in achieving much better recommendation quality in terms of aggregated diversity and novelty.  ...  In this work we describe how to create and exploit a knowledge graph to supply a hybrid recommendation engine with information that builds on top of a collections of documents describing musical and sound  ...  ACKNOWLEDGMENTS The authors would like to thank Gabriel Vigliensoni for providing the user's listening habits corpus.  ... 
doi:10.1145/2926718 fatcat:z4m4rqda65g45ju46j4dybyq3y

Optimization of an Intelligent Music-Playing System Based on Network Communication

Liaoyan Zhang, Zhihan Lv
2021 Complexity  
This paper describes in detail the working methods and contents of each stage of the real-time streaming music recommendation system, including requirement analysis, overall design, implementation of each  ...  Streaming media server is the core system of audio and video application in the Internet; it has a wide range of applications in music recommendation.  ...  For each tag, the paper calculated the amount of music tagged by it and the total number of times it was used. e analysis shows that there is a clear long-tail distribution of tag usage (Power Law Distribution  ... 
doi:10.1155/2021/9943795 fatcat:d2famaast5epba4rcfnu4greuy

Smarter Than Genius? Human Evaluation Of Music Recommender Systems

Luke Barrington, Reid Oda, Gert R. G. Lanckriet
2009 Zenodo  
However, Genius fails on music for which collaborative filtering data is unavailable, such as the huge volume of undiscovered content in the "long tail" of the music market.  ...  large "long tail" of new, undiscovered music.  ... 
doi:10.5281/zenodo.1417803 fatcat:jdzrcpdpz5akrerqfhbm2eagf4

Use of Deep Learning in Modern Recommendation System: A Summary of Recent Works

Ayush Singhal, Pradeep Sinha, Rakesh Pant
2017 International Journal of Computer Applications  
With the exponential increase in the amount of digital information over the internet, online shops, online music, video and image libraries, search engines and recommendation system have become the most  ...  We organize the review in three parts: Collaborative system, Content based system and Hybrid system.  ...  They use stacked denoising auto encoders to perform feature extraction for long-tail items or items which have very less content description as well as very less historical usage data.  ... 
doi:10.5120/ijca2017916055 fatcat:m6icpquumbgczhrdnya7x35of4

Music Information Technology and Professional Stakeholder Audiences: Mind the Adoption Gap

Cynthia C.S. Liem, Andreas Rauber, Thomas Lidy, Richard Lewis, Christopher Raphael, Joshua D. Reiss, Tim Crawford, Alan Hanjalic, Marc Herbstritt
2012 Dagstuhl Publications  
Thus, MIR technologies have the potential to have impact across disciplinary boundaries and to enhance the handling of music information in many different user communities.  ...  The academic discipline focusing on the processing and organization of digital music information, commonly known as Music Information Retrieval (MIR), has multidisciplinary roots and interests.  ...  However, in practice, only a tiny subset of the available content is seeing extreme usage, while the long tail beyond the popular artists is hardly consumed.  ... 
doi:10.4230/dfu.vol3.11041.227 dblp:conf/dagstuhl/LiemRLRRCH12 fatcat:zk5utpoaxbe6jptntrhw2rmf5q

Random Walk-based Recommendation with Restart using Social Information and Bayesian Transition Matrices

Suchit Pongnumkul, Kazuyuki Motohashi
2015 International Journal of Computer Applications  
Recommendation systems for incomplete data have become an active research area.  ...  The large number of products available today makes it impossible for any user to explore all of them and increases the importance of recommendation systems.  ...  Tagging, in which user-generated keywords are attached to online contents, is also used in recommendation systems, for example, to identify items to be retrieved in the future ( [22] , [23] , [24] ,  ... 
doi:10.5120/20009-1960 fatcat:fcsvhuwyzbed5hvx77svqpm5l4

Global and country-specific mainstreaminess measures: Definitions, analysis, and usage for improving personalized music recommendation systems

Christine Bauer, Markus Schedl, Chi Ho Yeung
2019 PLoS ONE  
Popularity-based approaches are widely adopted in music recommendation systems, both in industry and research.  ...  However, as the popularity distribution of music items typically is a long-tail distribution, popularity-based approaches to music recommendation fall short in satisfying listeners that have specialized  ...  Acknowledgments The authors would like to thank the Competence Center for Empirical Research Methods at WU Vienna for their support in the statistical analysis.  ... 
doi:10.1371/journal.pone.0217389 pmid:31173583 pmcid:PMC6555546 fatcat:egpr46g46vgpthgp4mccbbavau

A new collaborative filtering approach for increasing the aggregate diversity of recommender systems

Katja Niemann, Martin Wolpers
2013 Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13  
Such an approach also supports online-stores that often offer more items than traditional stores and need recommender systems to enable users to find the not so popular items as well.  ...  The approach increases the rating predictions for niche items with fewer usage data available and improves the aggregate diversity of the recommendations.  ...  INTRODUCTION Recommender systems are steadily becoming more important in an expanding number of domains (movies, music, books, etc.) to filter relevant items for users.  ... 
doi:10.1145/2487575.2487656 dblp:conf/kdd/NiemannW13 fatcat:plqs4lso4ngs7ap6jz4xstgjai

A Deep Multimodal Approach for Cold-start Music Recommendation

Sergio Oramas, Oriol Nieto, Mohamed Sordo, Xavier Serra
2017 Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems - DLRS 2017  
Music streaming services often ingest all available music, but this poses a challenge: how to recommend new artists for which prior knowledge is scarce?  ...  An increasing amount of digital music is being published daily.  ...  ACKNOWLEDGMENTS is work was partially funded by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502).  ... 
doi:10.1145/3125486.3125492 dblp:conf/recsys/OramasNSS17 fatcat:srv74edtavccnp46cqxgjptuxm

Local Music Event Recommendation with Long Tail Artists [article]

Douglas Turnbull, Luke Waldner
2018 arXiv   pre-print
In this paper, we explore the task of local music event recommendation. Many local artists tend to be obscure long-tail artists with a small digital footprint.  ...  That is, it can be hard to find social tag and artist similarity information for many of the artists who are playing shows in the local music community.  ...  This is an exciting task for the research community because it involves many interesting problems: long-tail recommendation, the new user & new artist cold start problems, multiple types of music information  ... 
arXiv:1809.02277v1 fatcat:xs4vzp2gsfa7roh537edooj3zi
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