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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Pinto, A. Haus, G. |
| Copyright Year | 2006 |
| Description | Author affiliation: Dipt. di Informatica e Comunicazione, Universita degli Studi di Milano (Pinto, A.; Haus, G.) |
| Abstract | Existing solutions for searching for appropriate music content rely on methods like string edit distances or functional approaches (as for the symbolic level) or features extraction methods (as for the audio level) that cannot provide structural similarity information. Our results in structural similarity measures for music information retrieval rely on graph theory and provide new tools for extract characterizing structural quantities from musical data (both symbolic and audio) to be implemented within an integrated query environment. The improvements regard the use of the graph model of musical data at different levels, the MX format for the representation of musical work and the new user interfaces for the navigation of musical source material |
| Starting Page | 266 |
| Ending Page | 272 |
| File Size | 1387980 |
| Page Count | 7 |
| File Format | |
| ISBN | 076952625X |
| DOI | 10.1109/AXMEDIS.2006.34 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-12-13 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Content based retrieval Navigation User interfaces Search engines Rhythm Feature extraction Graph theory Data mining Cultural differences Music information retrieval |
| Content Type | Text |
| Resource Type | Article |
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