Title :
Mining unusual data over data streams
Author :
Wei Xia ; Wei, Xia
Author_Institution :
Sch. of Comput. Sci., Huazhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
It is very important in many fields to mining the unusual data over the data streams. I propose algorithm MUD which are able to quickly and accurately find unusual data from the data streams. Recent works on sample method are not suitable for find the unusual data element from the data streams. In this paper, sample algorithm based on dissimilarity matrix is proposed. The extracted data element from data streams build trend of the unusual data with linear regression model. Experiments show that MUD is effective and the model works perfectly.
Keywords :
data mining; matrix algebra; regression analysis; MUD algorithm; data streams; dissimilarity matrix; linear regression model; unusual data mining; Computer science; Data mining; Data structures; Equations; Mathematics; Memory management; Monitoring; Multiuser detection; Reservoirs; Sampling methods; Data Streams; Dissimilarity Matrix; Mining Unusual Data; Regression Equation; Sample Algorithm;
Conference_Titel :
Future Computer and Communication (ICFCC), 2010 2nd International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5821-9
DOI :
10.1109/ICFCC.2010.5497508