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On the Influence of User Characteristics on Music Recommendation Algorithms [chapter]

Markus Schedl, David Hauger, Katayoun Farrahi, Marko Tkalčič
2015 Lecture Notes in Computer Science  
Overall, we find that the performance of music recommendation algorithms highly depends on user characteristics.  ...  Hypothesizing that user characteristics influence performance on these algorithmic combinations, we consider specific user groups determined by age, gender, country, and preferred genre.  ...  Acknowledgments This research is supported by the EU-FP7 project no. 601166 and by the Austrian Science Fund (FWF): P25655.  ... 
doi:10.1007/978-3-319-16354-3_37 fatcat:n2ex6s4jy5ehrgefvtoattseyi

Effects of personal characteristics on music recommender systems with different levels of controllability

Yucheng Jin, Nava Tintarev, Katrien Verbert
2018 Proceedings of the 12th ACM Conference on Recommender Systems - RecSys '18  
We designed a visual user interface, on top of a commercial music recommender, with different controls: interactions with recommendations (i.e., the output of a recommender system), the user profile (i.e  ...  Therefore, in this study, we investigate the effect of two personal characteristics: musical sophistication and visual memory capacity.  ...  ACKNOWLEDGEMENTS Part of this research has been supported by the KU Leuven Research Council (grant agreement C24/16/017).  ... 
doi:10.1145/3240323.3240358 dblp:conf/recsys/JinTV18 fatcat:tltk7ujdq5hpjdb3w335ghba3u


Yucheng Jin, Nyi Nyi Htun, Nava Tintarev, Katrien Verbert
2019 Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization - UMAP '19  
We also find that the contexts of mood, weather, and location tend to influence user perception of the system.  ...  By conducting a mixed-design study (N=114) with four typical scenarios of music listening, we investigate the effect of controlling contextual characteristics in a music recommender system on four aspects  ...  Existing research suggests that the influence of contextual characteristics on the functions of music listening outweighs the influence of personal characteristics [15, 16] .  ... 
doi:10.1145/3320435.3320445 dblp:conf/um/JinHTV19 fatcat:xbj7iy3zfjcsrctzgyp4jnwd7u

Effects of personal characteristics in control-oriented user interfaces for music recommender systems

Yucheng Jin, Nava Tintarev, Nyi Nyi Htun, Katrien Verbert
2019 User modeling and user-adapted interaction  
More specifically, we studied the influence of these characteristics on the design of (a) visualizations for enhancing recommendation diversity and (b) the optimal level of user controls while minimizing  ...  We found that (1) musical sophistication influenced the acceptance of recommendations for user controls. (2) musical sophistication also influenced recommendation acceptance, and perceived diversity for  ...  Acknowledgement This research has been supported by the KU Leuven Research Council (grant agreement C24/16/017).  ... 
doi:10.1007/s11257-019-09247-2 fatcat:nxchokl53vhjzf5kw3edzojkti

The Potential of the Confluence of Theoretical and Algorithmic Modeling in Music Recommendation [article]

Christine Bauer
2019 arXiv   pre-print
The task of a music recommender system is to predict what music item a particular user would like to listen to next.  ...  This position paper discusses the main challenges of the music preference prediction task: the lack of information on the many contextual factors influencing a user's music preferences in existing open  ...  ACKNOWLEDGMENTS This research is supported by the Austrian Science Fund V579.  ... 
arXiv:1911.07328v1 fatcat:p7jrrlgyajdthcft2jwwzj7d2m

Listener-Aware Music Recommendation from Sensor and Social Media Data [chapter]

Markus Schedl
2015 Lecture Notes in Computer Science  
In this note, we summarize our recent work and report our latest findings on the topics of tailoring music recommendations to individual listeners and to groups of listeners sharing certain characteristics  ...  We focus on two tasks: context-aware automatic playlist generation (also known as serial recommendation) using sensor data and music artist recommendation using social media data.  ...  The author would further like to thank his colleagues and students who contributed to the work at hand.  ... 
doi:10.1007/978-3-319-23461-8_16 fatcat:h4sjiiv52jfdtl3jdwkxt6tty4

Hybrid Variable-Scale Clustering Method for Social Media Marketing on User Generated Instant Music Video

2019 Tehnički Vjesnik  
Therefore, this paper studies the social media marketing problem of user generated instant music video.  ...  Social media has already become one of the mainstream enterprise marketing channels recently.  ...  Acknowledgements The study is supported by national natural science foundation of China (71272161) and China Scholarship Council.  ... 
doi:10.17559/tv-20190314152108 fatcat:utm7fpete5bxnmkei7hyi5gc2q

Using Factor Decomposition Machine Learning Method to Music Recommendation

Dapeng Sun, Zhihan Lv
2021 Complexity  
According to the implementation of the algorithm described in this article, the accuracy of the music recommendation results used to recommend user satisfaction is proved.  ...  The frequent pattern growth algorithm is compared with the association rule algorithm based on the collaborative filtering recommendation algorithm and the content-based recommendation algorithm, which  ...  Conflicts of Interest e authors declare that they have no known conflicts of interest or personal relationships that could have appeared to influence the work reported in this paper.  ... 
doi:10.1155/2021/9913727 fatcat:6diknz2k5famlgaigurtcam2tu

Improved Music Recommendation Algorithm for Deep Neural Network Based on Attention Mechanism

Xin He, Wen Zhou
2022 Mobile Information Systems  
Moreover, the traditional music recommendation algorithm only simply uses user behavior characteristics and does not make good use of user history for listening to audio characteristics.  ...  In view of the above question, this section based on the attention mechanism of the deep neural network music recommendation algorithm, through the use of improved MFCC audio data preprocessing, the extracted  ...  Based on this background, this paper based on the deep neural network, from the analysis of users, music characteristics, introduce attention mechanism, puts forward a personalized music recommendation  ... 
doi:10.1155/2022/4112575 fatcat:e2c23vwswbhqtiatqszvema2tu

Music Recommendation Algorithm Based on Multidimensional Time-Series Model Analysis

Juanjuan Shi
2021 Complexity  
Then, a music recommendation method is proposed, which integrates the long-term, medium-term, and real-time behaviors of users and considers the dynamic adjustment of the influence weight of the three  ...  so as to better predict the use of music users' behavior preference and give reasonable recommendations.  ...  However, the impact of such algorithms on the context of users is not enough to meet the immediate needs of users [23] . Music Recommendation Based on Midterm Behavior.  ... 
doi:10.1155/2021/5579086 doaj:2d7a1c54bd2e4d70833b3cc7f7937ec9 fatcat:k4sxd35d5bhe3nfaomgqtrelhq

Application of Collaborative Filtering and Data Mining Technology in Personalized National Music Recommendation and Teaching

Meilin Lu, Fangfang Deng, Chi-Hua Chen
2021 Security and Communication Networks  
Personalized music recommendations can accurately push the music of interest from a massive song library based on user information when the user's listening needs are blurred.  ...  To this end, this paper proposes a method of national music recommendation based on ontology modeling and context awareness to explore the use of music resources to portray user preferences better.  ...  Figure 6 shows the influence of time factors on the national music recommendation algorithm.  ... 
doi:10.1155/2021/3140341 fatcat:ifu7tintrbfg3dougzci6woaei

CBPF: leveraging context and content information for better recommendations [article]

Zahra Vahidi Ferdousi, Dario Colazzo, Elsa Negre
2018 arXiv   pre-print
In this paper we present an approach integrating contextual information into the recommendation process by modeling either item-based or user-based influence of the context on ratings, using the Pearson  ...  We evaluate and show effectiveness of our approach on three different contextual datasets and analyze the performances of the variants of our approach based on the characteristics of these datasets, especially  ...  In the former, characteristics of items/users are used to find and recommend similar items to the ones the user liked in the past.  ... 
arXiv:1810.00751v1 fatcat:z4hqvznosreqzdcc7m7ktrkhb4

Personal user interfaces for recommender systems

Martijn Millecamp, Katrien Verbert
2019 Proceedings of the 24th International Conference on Intelligent User Interfaces Companion - IUI '19  
In this Student Consortium submission, I outline the motivation and research questions of my PhD research on user interfaces for interacting with recommender systems, and particularly the interplay of  ...  different personal characteristics and effectiveness of different visualisation and interaction techniques.  ...  ACKNOWLEDGMENTS Part of this research has been supported by the KU Leuven Research Council (grant agreement C24/16/017).  ... 
doi:10.1145/3308557.3308729 dblp:conf/iui/MillecampV19 fatcat:nv7zzno7xvgdrmexho6voniboi

Multidimensional Analysis of Music Education System Based on Multi-Intelligent Recommendation

Daliang Wang, Xiaowen Guo, Le Sun
2022 Mobile Information Systems  
In the process of using this method to recommend music to users, the music characteristics are extracted and the music data are obtained from MIDI music, and three collaborative filtering algorithms are  ...  To better realize music education and improve the accuracy of music recommendation, a multidimensional analysis method of the music education system based on multi-intelligent recommendation is proposed  ...  Conflicts of Interest e authors declare that there are conflicts of interest regarding this work.  ... 
doi:10.1155/2022/8905999 fatcat:nwmryqh7bfhzznkq4aofwrw4iq

Variational Fuzzy Neural Network Algorithm for Music Intelligence Marketing Strategy Optimization

Juan Sun, Suneet Kumar Gupta
2022 Computational Intelligence and Neuroscience  
The basic idea of the recommendation algorithm is as follows: firstly, the historical behavioural information of music users is collected, and the user preference model is constructed by using the method  ...  In this paper, we use a variational fuzzy neural network algorithm to conduct an in-depth analysis and research on the optimization of music intelligent marketing strategy.  ...  In this chapter, based on describing the composition of user digital music information acquisition behaviour objects, the factors influencing user digital music information acquisition behaviour objects  ... 
doi:10.1155/2022/9051058 pmid:35035469 pmcid:PMC8758309 fatcat:qbbxr7rakzfvvdficmsfum6lre
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