User customized playlist generation based on music similarity

Playlist generation may be defined as the generation of a list of musical items or songs based on a pre-existing set of songs selected by the user. A common approach would be to suggest a number of songs based on the currently playing song. An exhaustive algorithm would involve computation of similarity of musical attributes of all of the songs with respect of the reference song. This paper introduces a methodology focused towards decreasing the computational complexity of such an algorithm. The suggested algorithm uses a distance function derived from a measure of similarity. This metric is cumulative and thus replaces complex calculations with operations involving only addition. Values of similarity are modified based on user feedback.