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A Preliminary Study on a Recommender System for the Million Songs Dataset Challenge

Fabio Aiolli
2013 Italian Information Retrieval Workshop  
In this paper, the preliminary study we have conducted on the Million Songs Dataset (MSD) challenge is described.  ...  The task of the competition was to suggest a set of songs to a user given half of its listening history and complete listening history of other 1 million people.  ...  We would like to thank the referees for their comments, which helped improve this paper considerably.  ... 
dblp:conf/iir/Aiolli13 fatcat:xjgk7xismrc3zmb2iwm7smvtoq

Using Adversarial Autoencoders for Multi-Modal Automatic Playlist Continuation

Iacopo Vagliano, Lukas Galke, Florian Mai, Ansgar Scherp
2018 Proceedings of the ACM Recommender Systems Challenge 2018 on - RecSys Challenge '18  
ACKNOWLEDGMENTS This work was supported by the German Research Foundation under project number 311018540 (Linked Open Citation Database) as well as by the EU H2020 project MOVING (contract no 693092).  ...  As preliminary experiments, we compared AAE on the Million Playlist Dataset in these more challenging settings against the baselines used in the previous experiments, i. e. item co-occurrence (IC) and  ...  However, these settings are more demanding than the challenge ones as they correspond to a new user scenario: the system has to recommend tracks for a playlist he has never seen before, which correspond  ... 
doi:10.1145/3267471.3267476 dblp:conf/recsys/VaglianoGMS18 fatcat:wzyqolzzizbd5e7fhsuksxkklu

#Nowplaying-Rs: A New Benchmark Dataset For Building Context-Aware Music Recommender Systems

Asmita Poddar, Eva Zangerle, Yi-Hsuan Yang
2018 Zenodo  
An increasing number of datasets have been compiled to facilitate research on different topics, such as content-based, context-based or next-song recommendation.  ...  Music recommender systems can offer users personalized and contextualized recommendation and are therefore important for music information retrieval.  ...  For example, this year, the RecSys Challenge 5 (as part of the ACM Recommender Systems Conference) also aims to perform a playlist continuation task and hence, sequence-based recommendations based on data  ... 
doi:10.5281/zenodo.1340994 fatcat:a7w5d75gwfgu3eiaqnct4hv22q

#Nowplaying-Rs: A New Benchmark Dataset For Building Context-Aware Music Recommender Systems

Asmita Poddar, Eva Zangerle, Yi-Hsuan Yang
2018 Zenodo  
An increasing number of datasets have been compiled to facilitate research on different topics, such as content-based, context-based or next-song recommendation.  ...  Music recommender systems can offer users personalized and contextualized recommendation and are therefore important for music information retrieval.  ...  For example, this year, the RecSys Challenge 5 (as part of the ACM Recommender Systems Conference) also aims to perform a playlist continuation task and hence, sequence-based recommendations based on data  ... 
doi:10.5281/zenodo.1318038 fatcat:m3xsc3fs7febhdajqpcwihiema

Report on RecSys 2014

Toine Bogers, Marijn Koolen, Iván Cantador
2015 SIGIR Forum  
The CBRecSys 2014 workshop aimed to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommender systems. 2  ...  For some domains, such as movies, the relationship between content and usage data has seen thorough investigation already, but for many other domains, such as books, news, scientific articles, and Web  ...  The proceedings were published as a CEUR Workshop Proceedings volume, available at http: //ceur-ws.org/Vol-1245/.  ... 
doi:10.1145/2795403.2795411 fatcat:ppva6ntbhbcpza7r34q6jiim2i

#Nowplaying-Rs: A New Benchmark Dataset For Building Context-Aware Music Recommender Systems

Asmita Poddar, Eva Zangerle, Yi-Hsuan Yang
2018 Proceedings of the SMC Conferences  
For example, this year, the RecSys Challenge 5 (as part of the ACM Recommender Systems Conference) also aims to perform a playlist continuation task and hence, sequence-based recommendations based on data  ...  Result on Context-aware Recommendation Result on Next-song Recommendation Table 6(b) shows the results obtained for context-aware next-song recommendation.  ... 
doi:10.5281/zenodo.1422565 fatcat:dh6trl5ngng63gspmghfld6oee

Deep Learning for Emotion Recognition in Affective Virtual Reality and Music Applications

2019 International journal of recent technology and engineering  
As such, the goal of this study is to perform a parameter tuning investigation on these deep parameters of the deep networks for predicting emotions in a virtual reality environment using electroencephalography  ...  The preliminary result showed a classification rate of 46.0%.  ...  As for dataset preparation, the larger the input layer to neural network, the better the system performs, and the use of limited song features indicates a more robust system.  ... 
doi:10.35940/ijrte.b1030.0782s219 fatcat:3utdzdkkxbhebnimqsl7na7auq

Song Clustering Using Peer-to-Peer Co-occurrences

Yuval Shavitt, Udi Weinsberg
2009 2009 11th IEEE International Symposium on Multimedia  
We present data collected from the Gnutella network and its properties and show two techniques for recommending content to users, one is based on clustering similar-minded users and the other creates song  ...  This results in songs that have similar properties to be shared together by many users, where the higher the number of song cooccurrences in different users, the stronger is the indication of a tight relationship  ...  These systems have been studied extensively in recent years (for an extensive study on music recommender † This research was supported in part by a grant from the Israel Science Foundation (ISF) center  ... 
doi:10.1109/ism.2009.84 dblp:conf/ism/ShavittW09 fatcat:jf4ijaoalbf2nh4zttwouavjt4

A Comparative Analysis of Personality-Based Music Recommender Systems

Melissa Onori, Alessandro Micarelli, Giuseppe Sansonetti
2016 ACM Conference on Recommender Systems  
This article describes a preliminary study on considering information about the target user's personality in music recommender systems (MRSs).  ...  For this purpose, we devised and implemented four MRSs and evaluated them on a sample of real users and real-world datasets.  ...  The authors sincerely thank Michal Kosinski, David Stillwell of the myPersonality project, and Liam McNamara for kindly providing the datasets used in the experimental evaluation.  ... 
dblp:conf/recsys/OnoriMS16 fatcat:n5dayrty2zelzbspnvjvgxhyru

Improving sales diversity by recommending users to items

Saúl Vargas, Pablo Castells
2014 Proceedings of the 8th ACM Conference on Recommender systems - RecSys '14  
Sales diversity is considered a key feature of Recommender Systems from a business perspective.  ...  Two experiments on movie and music recommendation datasets show the effectiveness of the resulting approach, even when compared to direct optimization approaches of the target metrics proposed in prior  ...  adjustment, we carry out two experiments on the Netflix Prize 2 and Million Song Dataset Challenge [10] datasets.  ... 
doi:10.1145/2645710.2645744 dblp:conf/recsys/VargasC14 fatcat:pd5snrotnvehtg7jehmjkcvkxi

Contextual music information retrieval and recommendation: State of the art and challenges

Marius Kaminskas, Francesco Ricci
2012 Computer Science Review  
This survey illustrates various tools and techniques that can be used for addressing the research challenges posed by context-aware music retrieval and recommendation.  ...  This survey covers a broad range of topics, starting from classical music information retrieval (MIR) and recommender system (RS) techniques, and then focusing on context-aware music applications as well  ...  The Million Song Dataset [137] is the latest effort to produce a large-scale dataset for MIR community.  ... 
doi:10.1016/j.cosrev.2012.04.002 fatcat:eheqwtlpufftni2k4sgolnskli

Context-Aware Recommender Systems in the Music Domain: A Systematic Literature Review

Álvaro Lozano Murciego, Diego M. Jiménez-Bravo, Adrián Valera Román, Juan F. De Paz Santana, María N. Moreno-García
2021 Electronics  
impact on the recommendations.  ...  The objective of this paper is to present a systematic literature review to analyze recent work to date in the field of context-aware recommender systems and specifically in the domain of music recommendation  ...  Acknowledgments: We are grateful to the University of Salamanca for supporting this work through the use of its facilities and providing access to bibliographic sources.  ... 
doi:10.3390/electronics10131555 fatcat:ehnvydv64rfbxghmf2kmrhdndq

Deep Content-User Embedding Model for Music Recommendation [article]

Jongpil Lee, Kyungyun Lee, Jiyoung Park, Jangyeon Park, Juhan Nam
2018 arXiv   pre-print
Recently deep learning based recommendation systems have been actively explored to solve the cold-start problem using a hybrid approach.  ...  We evaluate the model on music recommendation and music auto-tagging tasks. The results show that the proposed model significantly outperforms the previous work.  ...  The Echo Nest Taste Pro le Subset provides play count data for over 380,000 songs and one million users. The Last.fm dataset o ers tags for over 500,000 songs.  ... 
arXiv:1807.06786v1 fatcat:djezbsohvjfn3b5fta2qyt3ywy

Text-based Sentiment Analysis and Music Emotion Recognition [article]

Erion Çano
2018 arXiv   pre-print
Sentiment polarity of tweets, blog posts or product reviews has become highly attractive and is utilized in recommender systems, market predictions, business intelligence and more.  ...  This thesis addresses the above problems to provide methodological and practical insights for utilizing neural networks on sentiment analysis of texts and achieving state of the art results.  ...  RQ1 What studies addressing hybrid recommender systems are the most relevant? RQ2 What problems and challenges are faced by the researchers in this field?  ... 
arXiv:1810.03031v1 fatcat:4vj4euwtxbghbjdev2gutcgjny

Large-Scale Cover Song Detection in Digital Music Libraries Using Metadata, Lyrics and Audio Features [article]

Albin Andrew Correya, Romain Hennequin, Mickaël Arcos
2018 arXiv   pre-print
Our studies shows that these methods can significantly increase the accuracy and scalability of cover detection systems on Million Song Dataset (MSD) and Second Hand Song (SHS) datasets.  ...  Cover song detection is a very relevant task in Music Information Retrieval (MIR) studies and has been mainly addressed using audio-based systems.  ...  ACKNOWLEDGEMENTS The authors would like to thank Dr. Francesco Piccoli for the interesting discussions and reviews during this work.  ... 
arXiv:1808.10351v1 fatcat:awaw5wsgvzburobqcki47twc5q
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