Effective music searching approach based on tag combination by exploiting prototypical acoustic content
- Authors
- Lee, Jaesung; Chae, Jonghoon; Kim, Dae-Won
- Issue Date
- Feb-2017
- Publisher
- SPRINGER
- Keywords
- Music recommendation; Music tag; Acoustic feature; Associative tag mining
- Citation
- MULTIMEDIA TOOLS AND APPLICATIONS, v.76, no.4, pp 6065 - 6077
- Pages
- 13
- Journal Title
- MULTIMEDIA TOOLS AND APPLICATIONS
- Volume
- 76
- Number
- 4
- Start Page
- 6065
- End Page
- 6077
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/4884
- DOI
- 10.1007/s11042-016-3554-4
- ISSN
- 1380-7501
1573-7721
- Abstract
- Within the music information retrieval community, many studies and applications have focused on tag-based music categorization. The limitation in employing music tags is the ambiguity of each tag. Thus, a single music tag covers too many sub-categories. To circumvent this, multiple tags can be used simultaneously to specify music clips more precisely. However, in conventional music recommendation systems, this might not be achieved because music clips identified by the system might not be prototypical to both or each tag. In this paper, we propose a new technique for ranking proper tag combinations based on the acoustic similarity of music clips. Based on empirical experiments, proper tag combinations are suggested by our proto-typicality analysis.
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- Appears in
Collections - College of Software > Department of Artificial Intelligence > 1. Journal Articles
- College of Software > School of Computer Science and Engineering > 1. Journal Articles
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