Title
The review of outlier mining based on granular computing
Abstract
Outlier mining is an important part in data mining. In this paper, through the research of causes and detection methods of outlier, combined with the perspective of granular computing, we firstly present a general guiding principle of outlier mining that is granulation viewpoint, which shows that choosing reasonable granularity before granulation plays a very crucial role in outlier mining. Then we show a unified process frame diagram based on granular computing for outlier detection. Finally, a new algorithm based on granulation viewpoint for outlier detection is given. We argue that this paper can provide the practical reference value for the selection, improvement and the innovation of outlier detection method. And outlier mining based on granular computing will offer a kind of new thinking of research and analytic method for the future research topics and the challenges of the outlier mining.
Year
DOI
Venue
2008
10.1109/GRC.2008.4664651
GrC
Keywords
Field
DocType
outlier detection method,granularity,granular computing,data mining,outlier mining,granulation,algorithm design and analysis,outlier detection,unified process
Data mining,Anomaly detection,Algorithm design,Computer science,Unified Process,Outlier,Granular computing,Artificial intelligence,Granularity,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4244-2513-6
0
0.34
References 
Authors
9
3
Name
Order
Citations
PageRank
Shuang Liu100.34
Ji-yi Wang2178.05
Guolin Xing320.70