The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Social Tagging and Music Information Retrieval
Abstract
Social tags are free text labels that are applied to items such as artists, albums and songs. Captured in these tags is a great deal of information that is highly relevant to Music Information Retrieval (MIR) researchers including information about genre, mood, instrumentation, and quality. Unfortunately there is also a great deal of irrelevant information and noise in the tags. Imperfect as they may be, social tags are a source of human-generated contextual knowledge about music that may become an essential part of the solution to many MIR problems. In this article, we describe the state of the art in commercial and research social tagging systems for music. We describe how tags are collected and used in current systems. We explore some of the issues that are encountered when using tags, and we suggest possible areas of exploration for future research.
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Cites
Indexing by latent semantic analysis
Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990) · Journal of the American Society for Information Science · doi:10.1002/(sici)1097-4571(199009)41:6<391::aid-asi1>3.0.co;2-9 · Cited by 12,751
Term-weighting approaches in automatic text retrieval
Salton, G., & Buckley, C. (1988) · Information Processing & Management · doi:10.1016/0306-4573(88)90021-0 · Cited by 9,740
Labeling images with a computer game
von Ahn, L., & Dabbish, L. (2004) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/985692.985733 · Cited by 2,204
The vocabulary problem in human-system communication
Furnas, G. W., Landauer, T. K., Gomez, L. M., & Dumais, S. T. (1987) · Communications of the ACM · doi:10.1145/32206.32212 · Cited by 1,504
HT06, tagging paper, taxonomy, Flickr, academic article, to read
Marlow, C., Naaman, M., Boyd, D., & Davis, M. (2006) · Proceedings of the seventeenth conference on Hypertext and hypermedia · doi:10.1145/1149941.1149949 · Cited by 877
Popowich, F. (1999) · Wiley Encyclopedia of Electrical and Electronics Engineering · doi:10.1002/047134608x.w6910 · Cited by 834
Why we tag: motivations for annotation in mobile and online media
Ames, M., & Naaman, M. (2007) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240772 · Cited by 833
The role of transparency in recommender systems
Sinha, R., & Swearingen, K. (2002) · CHI '02 Extended Abstracts on Human Factors in Computing Systems · doi:10.1145/506443.506619 · Cited by 477
Automated Tag Clustering: Improving search and exploration in the tag space
Begelman, G., Keller, P., & Smadja, F. (2006) · Cited by 419
Representing Musical Genre: A State of the Art
Aucouturier, J.-J., & Pachet, F. (2003) · Journal of New Music Research · doi:10.1076/jnmr.32.1.83.16801 · Cited by 369
Cited by
Yahoo! music recommendations: modeling music ratings with temporal dynamics and item taxonomy
Koenigstein, N., Dror, G., & Koren, Y. (2011) · Proceedings of the fifth ACM conference on Recommender systems · doi:10.1145/2043932.2043964 · Cited by 273
Law, E., & von Ahn, L. (2009) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1518701.1518881 · Cited by 248
The Effects of Noisy Labels on Deep Convolutional Neural Networks for Music Tagging
Choi, K., Fazekas, G., Cho, K., & Sandler, M. (2018) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2017.2771298 · Cited by 42
Metadata
- Authors
- Lamere, P.
- Venue
- Journal of New Music Research
- Publisher
- Informa UK Limited
- Published
- 2008-06
- Volume
- 37
- Issue
- 2
- Pages
- 101-114
- ISSN
- 0929-8215 (ISSN-L)
- 1744-5027
- OpenAlex
- W1979955134
- Cited by
- 280
- References
- 21
- FWCI
- 40.40
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
