Paper Info
Title
Algorithm for Online Detection of the Data Stream Based on Distance.
Abstract
To address the inaccuracy and high time complexity of traditional data stream mining technology, this paper introduces a new algorithm of date detection based on k-distance to pruning and comentropy to detect sliding windows. When the data fills the current window, the k-distance of the data is used to prune all data in the pruning time. As a result, most normal data is filtered out. Experimental results demonstrate that the SWKC algorithm possesses better efficiency and accuracy than some other traditional detection algorithms.
Year
DOI
Venue
2015
10.3233/978-1-61499-619-4-397
Frontiers in Artificial Intelligence and Applications
Keywords
Field
DocType
sliding window,k-distance,anomaly detection,comentropy
Data stream clustering,Pattern recognition,Data stream,Computer science,Artificial intelligence
Conference
Volume
ISSN
Citations 
281
0922-6389
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Li-Ya Yu100.34
Jie Hu2131.34
Zhong-He Wei300.34
Guanci Yang4246.50