context-aware artist recommender system
CAARS: A Context-Aware Artist Recommender System for Twitter Users
Tang, Linh (Grinnell College ) | Hamid, Fahmida (Grinnell College)
In this work, we introduce a context-aware hybrid artist recommender system (CAARS) that uses Twitter users’ tweet-time patterns as context and users’ bias about gender and types of musicians to recommend artists. Our model offers a novel approach to improve a personalized music recommender system (MRS) as it extracts implicit information from the users’ past tweet-behavior and combines that with related content. The proposed model performs significantly better than collaborative and hybrid recommender systems and encourages further exploration.