A Survey of Music Personalized Recommendation System

DOI

10.2991/ncce-18.2018.141How to use a DOI?

Keywords

literature analysis; recommendation; ontology; contextual awareness.

Abstract

The study of music recommendation research was conducted and the corresponding research hotspots were proposed. The literature analysis method was used to briefly introduce the recommendation strategy from the perspective of the recommendation algorithm. It further proposes a method of using rough set theory to extract important context information and combines this user preference in context with collaborative filtering recommendation technology to implement a new idea of context recommendation-based music recommendation. The existing studies have a lack of systematic research on user behaviors and needs, low levels of feature extraction, and single problems in evaluation indicators. In the future, more in-depth discussions can be conducted in terms of group music recommendation, ontology modeling, and contextual awareness-based music recommendation in a mobile environment.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuan Xie
AU  - Lei Ding
PY  - 2018/05
DA  - 2018/05
TI  - A Survey of Music Personalized Recommendation System
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 852
EP  - 855
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.141
DO  - 10.2991/ncce-18.2018.141
ID  - Xie2018/05
ER  -