Skip to Main content Skip to Navigation
Conference papers

Interactive Music Recommendation System for Adapting Personal Affection: IMRAPA

Abstract : We have so various types of entertainment, and music is one of the most popular one. In this paper, we proposed music recommendation system that interactively adapts a user’s personal affection with only a simple operation, in which both acoustic and meta features are used. The more a user uses the proposed system, the better the system adapts the user’s personal affection and recommends the suitable songs. Through the evaluational experiment, we confirmed that the proposed system could recommend songs adapting user’s personal affection even if the personal affection variated.
Document type :
Conference papers
Complete list of metadatas

Cited literature [5 references]  Display  Hide  Download

https://hal.inria.fr/hal-01556186
Contributor : Hal Ifip <>
Submitted on : Tuesday, July 4, 2017 - 5:03:12 PM
Last modification on : Tuesday, July 4, 2017 - 5:35:46 PM
Long-term archiving on: : Friday, December 15, 2017 - 1:59:08 AM

File

978-3-642-33542-6_42_Chapter.p...
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Keigo Tada, Ryosuke Yamanishi, Shohei Kato. Interactive Music Recommendation System for Adapting Personal Affection: IMRAPA. 11th International Confernece on Entertainment Computing (ICEC), Sep 2012, Bremen, Germany. pp.417-420, ⟨10.1007/978-3-642-33542-6_42⟩. ⟨hal-01556186⟩

Share

Metrics

Record views

84

Files downloads

161