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Mostra: A Flexible Balancing Framework to Trade-off User, Artist and Platform Objectives for Music Sequencing [article]

Emanuele Bugliarello and Rishabh Mehrotra and James Kirk and Mounia Lalmas
2022 arXiv   pre-print
leads to a superior, just-in-time balancing across the various metrics of interest.  ...  We consider the task of sequencing tracks on music streaming platforms where the goal is to maximise not only user satisfaction, but also artist- and platform-centric objectives, needed to ensure long-term  ...  Music discovery: Users often have access to large repositories of music content with only a small fraction familiar to them.  ... 
arXiv:2204.10463v1 fatcat:wqgfxa56zfg3nmj2gh4fg5f6lu


Yuan Cao Zhang, Diarmuid Ó Séaghdha, Daniele Quercia, Tamas Jambor
2012 Proceedings of the fifth ACM international conference on Web search and data mining - WSDM '12  
Using a collection of novel algorithms inspired by principles of 'serendipitous discovery', we demonstrate a method of successfully injecting serendipity, novelty and diversity into recommendations whilst  ...  Recommendation systems exist to help users discover content in a large body of items.  ...  This work was in part funded by RCUK through the Horizon Digital Economy Research grant (EP/G065802/1).  ... 
doi:10.1145/2124295.2124300 dblp:conf/wsdm/ZhangSQJ12 fatcat:ajzweapzfvaqvfbsqbxcxm763e

Smarter Than Genius? Human Evaluation Of Music Recommender Systems

Luke Barrington, Reid Oda, Gert R. G. Lanckriet
2009 Zenodo  
Even systems that generate novel or serendipitous playlists for song discovery must include some familiar and relevant items to inspire users to trust the recommender system [3] .  ...  Balancing Content and Metadata Table 3 quantifies the competing influences of artist and acoustic similarity.  ... 
doi:10.5281/zenodo.1417803 fatcat:jdzrcpdpz5akrerqfhbm2eagf4

Risk "Attention" or "Adventure": A Qualitative Study of Novelty and Familiarity in Music Listening

Vikas Kumar, Sabirat Rubya, Joseph A. Konstan, Loren Terveen
2018 ACM Conference on Recommender Systems  
We show that a combination of factors, both explicit and implicit, such as boredom, need of attention, risk of a bad selection; that play in uential role in users' novel and familiar music selections.  ...  While recommendations systems have shown great improvements in generally predicting relevant items, they still face challenges in achieving the delicate balance between novel and familiar options.  ...  These factors thus play critical role in users' selection of music and the balance they seek in the amount of novelty or familiarity in their music.  ... 
dblp:conf/recsys/KumarRKT18 fatcat:efak6twzvzeybef4zoucylytse

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.  ...  Finally, we show how results of three different music recommendation technologies compare when applied to the task of finding similar artists to a seed artist.  ...  Using the API, we retrieved a list of tags with a normalized relevance value of 1..100 for each artist. 3. user profile lamere.  ... 
doi:10.1609/aimag.v32i3.2363 fatcat:wpnq6gltebch5leyee4rvhqpga

Evaluating Music Recommendations with Binary Feedback for Multiple Stakeholders [article]

Sasha Stoikov, Hongyi Wen
2021 arXiv   pre-print
High quality user feedback data is essential to training and evaluating a successful music recommendation system, particularly one that has to balance the needs of multiple stakeholders.  ...  Using the Piki Music dataset of 500k ratings collected over a two-year time period, we evaluate the performance of classic recommendation algorithms on three important stakeholders: consumers, well-known  ...  In the music domain, lesser-known artist have expressed many concerns, which include reaching an audience, transparency in recommendations, localizing discovery, gender balance and popularity bias, according  ... 
arXiv:2109.07692v1 fatcat:7ppjkcb5xncklguj36n7j3thum

Musical Similarity as Conceived by "Avid Recreational Music Listeners"

Jason Neal
2015 CAML Review / Revue de l ACBM  
It also considers prospects for incorporating actively nuanced dimensions of similarity into recommender systems, which could enable users to engage in cross-genre music discovery more easily than current  ...  This paper provides an overview of the contexts in which such trends have emerged.  ...  yield new music that piques their interest, or if it does not sustain an appropriate balance of familiarity and novelty.  ... 
doi:10.25071/1708-6701.40228 fatcat:ffa64y4lw5aezbzmhcz6ex7fue

"Play music": User motivations and expectations for non-specific voice queries

Jennifer Thom, Angela Nazarian, Ruth Brillman, Henriette Cramer, Sarah Mennicken
2020 Zenodo  
We conclude with implications for how these themes can inform the interaction design of voice search systems in handling non-specific music requests in voice search systems.  ...  The growing market of voice-enabled devices introduces new types of music search requests that can be more ambiguous than in typed search interfaces as voice assistants can potentially support conversational  ...  This was particularly marked with participants who expressed high degrees of confidence in the service's recommendation algorithms.  ... 
doi:10.5281/zenodo.4245523 fatcat:qptm4ox765bhrjc3zii4gwmeni


Mohsen Kamalzadeh, Christoph Kralj, Torsten Möller, Michael Sedlmair
2016 Proceedings of the 21st International Conference on Intelligent User Interfaces - IUI '16  
We report on the design and evaluation of TagFlip, a novel interface for active music discovery based on social tags of music.  ...  Contrary to conventional recommenders, which only allow the specification of seed attributes and the subsequent like/dislike of songs, we put the users in the centre of the recommendation process.  ...  The role of the user is, of course, not neglected in algorithmic recommender systems.  ... 
doi:10.1145/2856767.2856780 dblp:conf/iui/KamalzadehKMS16 fatcat:bmh2lgyl3fdctjcvypgclww5qq

Analysis and Exploitation of Musician Social Networks for Recommendation and Discovery

Ben Fields, Kurt Jacobson, Christophe Rhodes, Mark d'Inverno, Mark Sandler, Michael Casey
2011 IEEE transactions on multimedia  
These results are considered with a focus recommendation and discovery applications employing these hybrid measures as their basis.  ...  This paper presents an extensive analysis of a sample of a social network of musicians.  ...  similarity in music.  ... 
doi:10.1109/tmm.2011.2111365 fatcat:xsaocoaz35bpdmpowdiwks2pxi

A Novelty Search and Power-Law-Based Genetic Algorithm for Exploring Harmonic Spaces in J.S. Bach Chorales [chapter]

Bill Manaris, David Johnson, Yiorgos Vassilandonakis
2014 Lecture Notes in Computer Science  
We explore how novelty search can aid in the discovery of new harmonic progressions through this space as represented by a Markov model capturing probabilities of transitions between harmonies.  ...  It supports visual exploration and navigation of harmonic transition probabilities through interactive gesture control. These probabilities are computed from musical corpora (in MIDI format).  ...  This work has been supported in part by NSF (grants IIS-0736480, IIS-0849499 and IIS-1049554) and a donation from the Classical Music Archives.  ... 
doi:10.1007/978-3-662-44335-4_9 fatcat:otnsieqfinc6lfwmnm7bnqfdce

User Studies In The Music Information Retrieval Literature

David M. Weigl, Catherine Guastavino
2011 Zenodo  
Demographics and musical background, and familiarity with a particular piece, have been shown to impact on users' semantic descriptions of music [26] , further suggesting the usefulness of distinguishing  ...  algorithm to generate icons to be applied to the music files of the content they represent; this allows visual data mining of music collections from within the file listings of a standard computer operating  ... 
doi:10.5281/zenodo.1417811 fatcat:y6lc2oihrnfk5dgdrl34d2croi

Using knowledge anchors to facilitate user exploration of data graphs

Marwan Al-Tawil, Vania Dimitrova, Dhavalkumar Thakker, Krzysztof Janowicz
2019 Semantic Web Journal  
The implementation of the algorithm is applied in the context of a Semantic data browser in a music domain.  ...  We present several metrics for identifying KADG which are evaluated against familiar concepts in human cognitive structures.  ...  The MusicPinta semantic data browser was developed as part of the EU/FP7 project Dicode. We are grateful to the participants in the experimental studies.  ... 
doi:10.3233/sw-190347 fatcat:zytn3kcddjbm7elhau2rqf3oce

Collaborative Filtering Is Not Enough? Experiments with a Mixed-Model Recommender for Leisure Activities [chapter]

Nicolas Ducheneaut, Kurt Partridge, Qingfeng Huang, Bob Price, Mike Roberts, Ed H. Chi, Victoria Bellotti, Bo Begole
2009 Lecture Notes in Computer Science  
In this paper, we present results from an experiment assessing user satisfaction with recommendations for leisure activities that are obtained from different combinations of these techniques.  ...  Collaborative filtering (CF) is at the heart of most successful recommender systems nowadays.  ...  They have proven effective at recommending content such as movies, books, music, and other kinds of products [18] .  ... 
doi:10.1007/978-3-642-02247-0_28 fatcat:thktwtavsbdafkxico52bsksx4

Effects of recommendations on the playlist creation behavior of users

Iman Kamehkhosh, Geoffray Bonnin, Dietmar Jannach
2019 User modeling and user-adapted interaction  
Today, much of the music that we listen to is organized in some form of a playlist, and many users of modern music platforms create playlists for themselves or to share them with others.  ...  Finally, our study also reveals that the mere presence of the recommendations impacts the choices of the participants, even in cases when none of the recommendations was actually chosen.  ...  Acknowledgements Open access funding provided by University of Klagenfurt.  ... 
doi:10.1007/s11257-019-09237-4 fatcat:s4d5k4uaybag7ftb2v3fzbfkvi
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