@INPROCEEDINGS { Rsds4659,
author = {Chen, Yuming and Miao, Duoqian and Wang, Ruizhi}, 
title = {Outlier Detection Based on Granular Computing}, 
booktitle = {Proceedings of the Sixth International Conference on Rough Sets and Current Trends in Computing (RSCTC'2008)}, 
conference = {Rough Sets and Current Trends in Computing}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 5306, 
pages = {283--292}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
month = {November}, 
year = 2008, 
abstract = {As an emerging conceptual and computing paradigm of information processing, granular computing has received much attention recently. Many models and methods of granular computing have been proposed and studied. Among them was the granular computing model using information tables. In this paper, we shall demonstrate the application of this granular computing model for the study of a specific data mining problem - outlier detection. Within the granular computing model using information tables, this paper proposes a novel definition of outliers - GrC (granular computing)-based outliers. An algorithm to find such outliers is also given. And the effectiveness of GrC-based method for outlier detection is demonstrated on three publicly available databases.}, 
keywords = {granular computing, outlier detection, rough sets, data mining, }, 
}