scholarly journals PlayMyMood: Personalized Hybrid Music Recommendation Engine based on Body Monitoring Parameters

2021 ◽  
Author(s):  
Aditya Vinod Kumar
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Hierarchical Model ◽  
Recommendation System ◽  
Music Recommendation ◽  
Body Parameters ◽  
Music Recommendation System

In this paper, we build a hybrid personalized music recommendation system that takes into account the user's previous listening history, real-time body parameters such as heart rate and interest of similar users. We build a unique unsupervised hierarchical model that combines all these attributes and computes the best song recommendation to the user.

scholarly journals PlayMyMood: Personalized Hybrid Music Recommendation Engine based on Body Monitoring Parameters

2021 ◽  
Author(s):  
Aditya Vinod Kumar
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Hierarchical Model ◽  
Recommendation System ◽  
Music Recommendation ◽  
Body Parameters ◽  
Music Recommendation System

In this paper, we build a hybrid personalized music recommendation system that takes into account the user's previous listening history, real-time body parameters such as heart rate and interest of similar users. We build a unique unsupervised hierarchical model that combines all these attributes and computes the best song recommendation to the user.

scholarly journals Neural Collaborative For Music Recommendation System

2021 ◽  
Vol 1071 (1) ◽  
pp. 012021
Author(s):  
Abba Suganda Girsang ◽  
Antoni Wibowo ◽  
Jason ◽  
Roslynlia
Keyword(s):  
Recommendation System ◽  
Music Recommendation ◽  
Music Recommendation System

Song Recommendations Based on Artists with Cosine Similarity Algorithms and K-Nearest Neighbor

2020 ◽  
Vol 8 (4) ◽  
pp. 367
Author(s):  
Muhammad Arief Budiman ◽  
Gst. Ayu Vida Mastrika Giri
Keyword(s):  
Collaborative Filtering ◽  
Mobile Phones ◽  
Recommendation System ◽  
Nearest Neighbor ◽  
Cosine Similarity ◽  
Music Recommendation ◽  
K Nearest Neighbor ◽  
Filtering Method ◽  
K Nearest Neighbor Algorithm ◽  
Music Recommendation System

The development of the music industry is currently growing rapidly, millions of music works continue to be issued by various music artists. As for the technologies also follows these developments, examples are mobile phones applications that have music subscription services, namely Spotify, Joox, GrooveShark, and others. Application-based services are increasingly in demand by users for streaming music, free or paid. In this paper, a music recommendation system is proposed, which the system itself can recommend songs based on the similarity of the artist that the user likes or has heard. This research uses Collaborative Filtering method with Cosine Similarity and K-Nearest Neighbor algorithm. From this research, a system that can recommend songs based on artists who are related to one another is generated.

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