Common Artist Music Assistance

TL;DR

This paper presents a recommendation system tailored for users with common-artist listening patterns, utilizing the 'random walk with restart' algorithm to improve music content relevance based on user interests.

Contribution

It introduces a novel recommendation approach specifically designed for users sharing artist preferences, optimizing parameter settings through experimental analysis.

Findings

Effective recommendations for users with common-artist listening patterns

Optimal parameter values identified for the 'random walk with restart' algorithm

Improved relevance in music suggestions based on user interests

Abstract

In today's world of growing number of songs, the need of finding apposite music content according to a user's interest is crucial. Furthermore, recommendations suitable to one user may be irrelevant to another. In this paper, we propose a recommendation system for users with common-artist music listening patterns. We use "random walk with restart" algorithm to get relevant recommendations and conduct experiments to find the optimal values of multiple parameters.