Personalized Music Recommendation with Triplet Network
Information Retrieval
2019-08-13 v1 Machine Learning
Multimedia
Abstract
Since many online music services emerged in recent years so that effective music recommendation systems are desirable. Some common problems in recommendation system like feature representations, distance measure and cold start problems are also challenges for music recommendation. In this paper, I proposed a triplet neural network, exploiting both positive and negative samples to learn the representation and distance measure between users and items, to solve the recommendation task.
Cite
@article{arxiv.1908.03738,
title = {Personalized Music Recommendation with Triplet Network},
author = {Haoting Liang and Donghuo Zeng and Yi Yu and Keizo Oyama},
journal= {arXiv preprint arXiv:1908.03738},
year = {2019}
}
Comments
1 figure; 1 table