Heartbeats: music recommendation system with fuzzy inference engine
Vinothini Kasinathan,Aida Mustapha,Tan Sau Tong,Mohamad Firdaus Che Abdul Rani,Nor Azlina Abd Rahman +4 more
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TLDR
Findings of the this paper have shown that Heartbeats’s fuzzy inference engine has successfully achieved its aim, which is to improve users’ music listening experience by giving suitable song recommendation based on user context situation.Abstract:
In developing a music recommendation system, there are several factors that can contribute to the inefficiency in music selection. One of the problems persists during the music listening is that common music playing application lacks the ability to acquire context of the user. Another problem that common music recommendation system fails to address the is emotional impact of the recommended song. To address this gap, this paper presents a music recommendation system based on fuzzy inference engine that considers user activities and emotion as part of the recommendation parameters. The system includes building a smart music recommendation system that has user profiling capabilities to recommend correct songs based on the user’s preferences, mood and time. Findings of the this paper have shown that Heartbeats’s fuzzy inference engine has successfully achieved its aim, which is to improve users’ music listening experience by giving suitable song recommendation based on user context situation.read more
Citations
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Journal ArticleDOI
Considering emotions and contextual factors in music recommendation: a systematic literature review
TL;DR: A systematic literature review as discussed by the authors investigated the music recommendation approaches that consider emotions and/or context (research question 1) as well as to identify the main gaps and challenges that still need to be addressed by future research.
Journal ArticleDOI
Creating Music With Fuzzy Logic.
TL;DR: It is proposed that fuzzy logic is a very suitable framework for thinking and operating not only with sound and acoustic signals but also with symbolic representations of music.
Proceedings Article
A Review on the use of Machine Learning Techniques in Music Recommendation System for Healthcare Management
TL;DR: In this paper , a survey of various machine learning techniques and its types utilized in recommendation of music for health care management is presented. And the classification accuracy is considered as a key parameter to define the effectiveness of music recommendation systems.
References
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Efficient music recommender system using context graph and particle swarm
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