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Combining usage and content in an online music recommendation system for music in the long-tail
2012
Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion
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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
2012
International Journal of Multimedia Information Retrieval
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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
2013
International Journal of Multimedia Information Retrieval
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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
2011
The AI Magazine
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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
2020
Zenodo
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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
2016
ACM Transactions on Intelligent Systems and Technology
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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
2021
Complexity
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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
2009
Zenodo
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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
2017
International Journal of Computer Applications
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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
2012
Dagstuhl Publications
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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
2015
International Journal of Computer Applications
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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
2019
PLoS ONE
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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
2013
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13
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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
2017
Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems - DLRS 2017
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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]
2018
arXiv
pre-print
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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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