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Sociology And Music Recommendation Systems

Daniel McEnnis, Sally Jo Cunningham
2007 Zenodo  
MUSIC RECOMMENDATION SYSTEMS There have been a number of music recommendation systems proposed.  ... is a commercial example of a content-based recommendation system. Two of Chen and Chen's [3] recommendation algorithms utilize purely content-based approaches.  ... 
doi:10.5281/zenodo.1414854 fatcat:xn2ejr2om5ft5dtutb57trvf4e

Emotion Based Music Recommendation System

Mikhail Rumiantcev, Oleksiy Khriyenko
2020 Zenodo  
Recommendation systems gain more and more popularity and help people to select appropriate music for all occasions.  ...  This paper will present design of the personalized music recommendation system, driven by listener feelings, emotions and activity contexts.  ...  In this work we present the design of the personalized emotion-driven music recommendation system.  ... 
doi:10.5281/zenodo.4007449 fatcat:4hnpkero5vhbfj4hrprrlh7mpi

Psychologically-Inspired Music Recommendation System [article]

Danila Rozhevskii, Jie Zhu, Boyuan Zhao
2022 arXiv   pre-print
In the last few years, automated recommendation systems have been a major focus in the music field, where companies such as Spotify, Amazon, and Apple are competing in the ability to generate the most  ...  Our goal is to find a way to integrate users' personal traits and their current emotional state into a single music recommendation system with both collaborative and content-based filtering.  ...  If we manage to achieve that, we could bring music recommendation systems to a whole new state-of-the-art level [12] .  ... 
arXiv:2205.03459v1 fatcat:65sk7sznjjfytpa52vterdejom

Emotion Based Music Recommendation System

Dhruv Piyush Parikh
2021 International Journal for Research in Applied Science and Engineering Technology  
In such difficult circumstances, it became necessary for us to devise a system that would assist the people in expressing what they truly feel.  ...  So, the idea is to automate tasks that the human visual systems can do. Neuropsychiatric symptoms appear to be common in people due to covid-19.  ... 
doi:10.22214/ijraset.2021.38655 fatcat:f5dxa7xvvbcmrk4zkcoux2escy

Context-aware music recommender systems

Francesco Ricci
2012 Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion  
These topics will be illustrated in the talk, making examples taken from the music recommender systems that our research team has developed.  ...  However, notwithstanding the fact that music recommender systems are among the most common applications of recommendation techniques, there are very few music recommender systems that are capable to adapt  ...  Context-aware music recommender systems can benefit from a number of techniques and methodologies that have been proposed, developed, and tested in the larger scope of context-aware recommender systems  ... 
doi:10.1145/2187980.2188215 dblp:conf/www/Ricci12 fatcat:ktqv6jivtvdj3ddeoupakpjgry

Music Recommender System Using ChatBot

Shivam Sakore
2021 International Journal for Research in Applied Science and Engineering Technology  
Abstract: In this era of technological advances, text-based music recommendations are much needed as they will help humans relieve stress with soothing music according to their moods.  ...  In this project, we have implemented a chatbot that recommends music based on the user's text tone. By analyzing the tone of the text expressed by the user, we can identify the mood.  ...  A number of live online music recommender systems exist, each using its own methodology to suggest music.  ... 
doi:10.22214/ijraset.2021.39717 fatcat:ylggk6oxmja4pj6yfj5qodr3h4

Explainability in Music Recommender Systems [article]

Darius Afchar, Alessandro B. Melchiorre, Markus Schedl, Romain Hennequin, Elena V. Epure, Manuel Moussallam
2022 arXiv   pre-print
To assist users in effectively browsing these large catalogs, the integration of Music Recommender Systems (MRSs) has become essential.  ...  Finally, we describe the current challenges for introducing explainability within a large-scale industrial music recommender system and provide research perspectives.  ...  Characteristics of music consumption and music recommender systems While music recommendation shares some properties with other media recommendation tasks, such as videos or movies, there exist also pronounced  ... 
arXiv:2201.10528v1 fatcat:k4mhwh2nhzexxgyvz3dppv3j5i

Deep Learning in Music Recommendation Systems

Markus Schedl
2019 Frontiers in Applied Mathematics and Statistics  
Like in many other research areas, deep learning (DL) is increasingly adopted in music recommendation systems (MRS).  ...  music recommendation).  ...  INTRODUCTION Research on music recommendation systems (MRS) is spiraling [1] . So is research in deep learning (DL).  ... 
doi:10.3389/fams.2019.00044 fatcat:vvosxlygrravloyrj3qubflnoe

Multiple Stakeholders in Music Recommender Systems [article]

Himan Abdollahpouri, Steve Essinger
2017 arXiv   pre-print
Music recommendation services collectively spin billions of songs for millions of listeners on a daily basis.  ...  These stakeholders each have their own objectives and must work in concert to sustain a healthy music recommendation service.  ...  STAKEHOLDERS IN MUSIC RECOMMENDER SYSTEMS Pandora is one of the world's largest music recommendation companies in terms of active users and songs recommended. e platform consists of a variety of di erent  ... 
arXiv:1708.00120v1 fatcat:64irqhofpbffdmlcixsdb65ysm

Music Recommendation System Using Machine Learning

Varsha Verma, Ninad Marathe, Parth Sanghavi, Dr. Prashant Nitnaware
2021 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
Along with this,a front end with flask that will show us the recommended songs when a specific song is processed.  ...  In our project, we will be using a sample data set of songs to find correlations between users and songs so that a new song will be recommended to them based on their previous history.  ...  Thus, there is а strоng need fоr а gооd recommendation system. Recommendation Systems аre everywhere аnd рretty stаndаrd аll оver the web.  ... 
doi:10.32628/cseit217615 fatcat:fvlnyvlt3zav5kxjxvrtqwrnh4

Evaluating Music Recommender Systems for Groups [article]

Zsolt Mezei, Carsten Eickhoff
2017 arXiv   pre-print
Using this benchmarking dataset, that we share with the research community, we compare the respective performance of a wide range of music group recommendation techniques proposed in the  ...  Recommendation to groups of users is a challenging and currently only passingly studied task.  ...  Finally, on the basis of our collection, Section 4 compares a wide range of existing music group recommendation systems as well as basic machine learning algorithms.  ... 
arXiv:1707.09790v1 fatcat:x27xl7pu2najhmkibvdbttg5l4

Muse: A Music Recommendation Management System

Martin Przyjaciel-Zablocki, Thomas Hornung 0001, Alexander Schätzle, Sven Gauß, Io Taxidou, Georg Lausen
2014 Zenodo  
MUSE OVERVIEW We propose MUSE: a web-based music recommendation management system, built around the idea of recommenders that can be plugged in.  ...  A schematic overview of the whole system is depicted in Fig. 1 . The MUSE Server is the core of our music recommendation management system enabling the communication between all components.  ... 
doi:10.5281/zenodo.1418194 fatcat:3tcdqtw3kngfrb6mka3hlzsyhq


Freeman Sophie Olivia
2019 Selected Papers of Internet Research, SPIR  
We trust music streaming and recommender systems like Spotify to 'set the mood' for us, to soundtrack our private lives and activities, to recommend & discover for us.  ...  This paper builds on research which critically examined the music recommendation system that powers Spotify and its many discovery features.  ...  In what way do music recommender systems bear the imprint of the developers that built them? What tacit music knowledge exists, or indeed, pre-exists the music recommender system?  ... 
doi:10.5210/spir.v2019i0.10962 fatcat:nvyxekb2r5f4vgfulhb6kiia3i

Exploring Gender Distribution in Music Recommender Systems

Dougal Shakespeare, Lorenzo Porcaro, Emilia Gómez
2020 Zenodo  
Music Recommender Systems (mRS) are designed to give personalised and meaning-ful recommendations of items (i.e. songs, playlists or artists) to a user base, thereby reflecting and further complementing  ...  individual users' specific music preferences.  ...  Music Recommender Systems Music Recommender Systems are a subdivision of RS whereby the items being recommended consist of musical content.  ... 
doi:10.5281/zenodo.4091510 fatcat:5ug2dprnr5haxgfukjtpofnlxe


Meghan Patil, Sainaya Brid, Stuti Dhebar
2020 International Journal of Engineering Applied Sciences and Technology  
Keywords-Music recommendation system, machine learning, deep learning, neural network. I.  ...  Recommendation systems have become very popular and an essential part of consumer-based systems such as shopping, music, movies, etc.  ...  In the context of the recommender system, SVD is used as a collaborative filtering technique.  ... 
doi:10.33564/ijeast.2020.v05i06.036 fatcat:yphebgpswfh2rbg52354bpm6tq
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