@INPROCEEDINGS { Rsds2732,
author = {Hippe, Monika P.}, 
title = {Towards the Classification of Musical Works: A Rough Set Approach}, 
booktitle = {Rough Sets and Current Trends in Computing}, 
conference = {Rough Sets and Current Trends in Computing}, 
series =  = {Lecture Notes in Arificial Intelligence}, 
volume = 2475, 
pages = {546--553}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
month = {October}, 
year = 2002, 
editor = {Alpigini, James J. and Peters, James F. and Skowron, Andrzej and Zhong, Ning Liu Jiming}, 
issn = {0302-9743}, 
isbn = {3-540-44274-X}, 
abstract = {This paper suggests an approach to classifying musical works using a rough set approach. Base on a review of available literature devoted to applications of programming tools in studying mechanisms of music perception, the paper focuses on discovering hidden regularities in pieces of various types of music. This work is motivated by an interest in determining the influences of one composer on other composers. A brief overview of rough set methods underlying this study is presented. We also report a variety of different experiments that have been performed on some sample data extracted from musical compositions. The contribution of this paper is the identification of a set of attributes that can be used to classify musical works with a considerable accuracy.}, 
keywords = {attributes of music, attribute reduction, classify, decomposition tree, discretization, inference rules, rough sets, }, 
}