On-demand metadata extraction network (OMEN)

منو

" On-demand metadata extraction network (OMEN) "
Daniel McEnnis

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	52795
Doc. No	:	TL22749
Call number	:	‭MR28567‬
Main Entry	:	Daniel McEnnis
Title & Author	:	On-demand metadata extraction network (OMEN)\ Daniel McEnnis
College	:	McGill University (Canada)
Date	:	2006
Degree	:	M.A.
student score	:	2006
Page No	:	80
Abstract	:	OMEN (On-demand Metadata Extraction Network) addresses a fundamental problem in Music Information Retrieval: the lack of universal access to a large dataset containing significant amounts of copyrighted music. This thesis proposes a solution to this problem that is accomplished by utilizing the large collections of digitized music available at many libraries. Using OMEN, libraries will be able to perform on-demand feature extraction on site, returning feature values to researchers instead of providing direct access to the recordings themselves. This avoids copyright difficulties, since the underlying music never leaves the library that owns it. The analysis is performed using grid-style computation on library machines that are otherwise under-used (e.g., devoted to patron web and catalogue use).
Subject	:	Communication and the arts; Music; Information systems; 0413:Music; 0723:Information systems
Added Entry	:	McGill University (Canada)