Add to ORKGThis study explores the presence of optimal differentiation in music at the feature level by genre. Popularity prediction models are constructed and used to identify influential features in predicting popularity in each genre. These influential features are then assessed for optimal differentiation of the most popular songs from all songs in the genre
The modern ability to stream music using services such as Spotify, Pandora, and Apple music has revo...
Data mining techniques recently were used to solve several problems related to music. This dissertat...
Humans identify with three basic components of music: melody, harmony, and rhythm, in order to descr...
This study explores the presence of optimal differentiation in music at the feature level by genre. ...
The growing use of predictive analysis can be seen in volatile industries such as the music industry...
In late 20th and early 21st century Western popular music, there are cyclical structures, sounds, an...
Forecasting the popularity of new songs has become a standard practice in the music industry and pro...
Music streaming services like Spotify have changed the way consumers listen to music. Understanding ...
Digital music distribution is increasingly powered by automated mechanisms that continuously capture...
This paper uses the data crawled from the AllMusic website to establish a directional network of fol...
Music has tremendous cultural and commercial significance for people the world over. It is one of th...
Abstract. The possibility of a hit song prediction algorithm is both academically inter-esting and i...
This research aims to analyze the effect of feature selection on the accuracy of music popularity cl...
Research in Featuring Engineering has been part of the data pre-processing phase of machine learning...
Consumers widely use music genres (e.g., pop, rock) for finding the right products. However, they ar...
The modern ability to stream music using services such as Spotify, Pandora, and Apple music has revo...
Data mining techniques recently were used to solve several problems related to music. This dissertat...
Humans identify with three basic components of music: melody, harmony, and rhythm, in order to descr...
This study explores the presence of optimal differentiation in music at the feature level by genre. ...
The growing use of predictive analysis can be seen in volatile industries such as the music industry...
In late 20th and early 21st century Western popular music, there are cyclical structures, sounds, an...
Forecasting the popularity of new songs has become a standard practice in the music industry and pro...
Music streaming services like Spotify have changed the way consumers listen to music. Understanding ...
Digital music distribution is increasingly powered by automated mechanisms that continuously capture...
This paper uses the data crawled from the AllMusic website to establish a directional network of fol...
Music has tremendous cultural and commercial significance for people the world over. It is one of th...
Abstract. The possibility of a hit song prediction algorithm is both academically inter-esting and i...
This research aims to analyze the effect of feature selection on the accuracy of music popularity cl...
Research in Featuring Engineering has been part of the data pre-processing phase of machine learning...
Consumers widely use music genres (e.g., pop, rock) for finding the right products. However, they ar...
The modern ability to stream music using services such as Spotify, Pandora, and Apple music has revo...
Data mining techniques recently were used to solve several problems related to music. This dissertat...
Humans identify with three basic components of music: melody, harmony, and rhythm, in order to descr...