Neural Network Based Next-Song Recommendation
This work addresses the need for improved sequential recommendation in music streaming services, but it is incremental as it builds on existing neural network and NLP methods.
The authors tackled the problem of next-song recommendation by proposing CNN-rec, a neural network model inspired by NLP techniques, which outperformed classic systems and achieved comparable performance to the state-of-the-art.
Recently, the next-item/basket recommendation system, which considers the sequential relation between bought items, has drawn attention of researchers. The utilization of sequential patterns has boosted performance on several kinds of recommendation tasks. Inspired by natural language processing (NLP) techniques, we propose a novel neural network (NN) based next-song recommender, CNN-rec, in this paper. Then, we compare the proposed system with several NN based and classic recommendation systems on the next-song recommendation task. Verification results indicate the proposed system outperforms classic systems and has comparable performance with the state-of-the-art system.