Please use this identifier to cite or link to this item: http://hdl.handle.net/1901/205
Full metadata record
| DC Field | Value | Language |
|---|---|---|
| contributor.advisor | Stephanie W. Haas | en |
| creator | William P. Hannah | en |
| date.accessioned | 2005-05-17T15:42:42Z | - |
| date.available | 2005-05-17 | en |
| date.issued | 2005-05-17T15:42:42Z | - |
| date.submitted | May 13, 2005 | en |
| identifier.uri | http://hdl.handle.net/1901/205 | - |
| description.abstract | This paper describes a two-part study attempting to correlate music genre assignments performed by two primary, yet disparate groups: the music industry and consumers of popular music. An online survey was conducted, aimed at evaluating the latter group's perception of music genre. The sample of the survey consisted of 15 UNC-CH students affiliated with the music department. Concurrently, a series of genre classification experiments were conducted on several corpora of music reviews harvested from authoritative, online review websites. Results of the survey were subsequently triangulated with a portion of the music review corpora in a final genre classification experiment. The genre classification experiments were quite successful, yielding a maximum of 91% accuracy using web-based data alone. The effect of weighting schemes and procedural modifications on experimental accuracy rates are discussed, as are qualitative evaluations of participants' responses to the survey. | en |
| format | application/pdf | en |
| format.extent | 374767 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en_US | en |
| publisher | School of Information and Library Science | en |
| rights | Attribution-NonCommercial 1.0 | en |
| subject | Automation of Library Processes – Classification/Automation Automation of Library Processes – Music Libraries and Collections/Automation Music Information Retrieval – Music Genre Classification Music Information Retrieval – User Needs Evaluation Indexing – Automatic Indexing | en |
| title | Automated Music Genre Classification Based on Analyses of Web-Based Documents and Listeners’ Organizational Schemes. | en |
| type | Electronic Theses and Dissertations | en |
| degree.discipline | Library Science | en |
| degree.grantor | University of North Carolina at Chapel Hill | en |
| degree.level | Master | en |
| degree.name | Master of Science | en |
| Appears in Collections: | SILS Master's Papers |
Files in This Item:
|
All items in SILS-ETD are protected by copyright, with all rights reserved.