@INPROCEEDINGS { Rsds4511,
author = {Miao, Duoqian and Chen, Min and Lingras, Pawan J.}, 
title = {Rough Multi-category Decision Theoretic Framework}, 
booktitle = {Proceedings of the Third International Conference on Rough Sets and Knowledge Technology (RSKT'2008)}, 
conference = {Rough Sets and Knowledge Technology}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 5009, 
pages = {676--683}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
month = {May}, 
year = 2008, 
editor = {Wang, Guoying and Li, Tianrui and Grzymala-Busse, Jerzy W. and Miao, Duoqian and Skowron, Andrzej and Yao, Yiyu}, 
issn = {03029743}, 
isbn = {978-3-540-69069-6}, 
abstract = {Decision theoretic framework has been helpful in providing a better understanding of classification models. In particular, decision theoretic interpretations of different types of the binary rough set classification model have led to the refinement of these models. This study extends the decision theoretic rough set model to supervised and unsupervised multi-category problems. The proposed framework can be used to study the multi-classification and clustering problems within the context of rough set theory.}, 
keywords = {rough sets, Web usage mining, rough approximation, k-means cluster algorithm, }, 
}