Geographical Region Mapping Scheme Based on Musical Preferences

Many countries and cities in the world tend to have different types of preferred or popular music, such as pop, K-pop, and reggae. Music-related applications utilize geographical proximity for evaluating the similarity of music preferences between two regions. Sometimes, this can lead to incorrect results due to other factors such as culture and religion. To solve this problem, in this paper, we propose a scheme for constructing a music map in which regions are positioned close to one another depending on the similarity of the musical preferences of their populations. That is, countries or cities in a traditional map are rearranged in the music map such that regions with similar musical preferences are close to one another. To do this, we collect users’ music play history and extract popular artists and tag information from the collected data. Similarities among regions are calculated using the tags and their frequencies. And then, an iterative algorithm for rearranging the regions into a music map is applied. We present a method for constructing the music map along with some experimental results.