Outlier detection for high-dimensional data streams
Paper
Zhang, Ji, Gao, Qigang and Wang, Hai. 2007. "Outlier detection for high-dimensional data streams." 5th Dalhousie Computer Science In-house Conference (DCSI'07). Halifax, Canada 05 Apr 2007 Halifax, Nova Scotia, Canada.
Paper/Presentation Title | Outlier detection for high-dimensional data streams |
---|---|
Presentation Type | Paper |
Authors | Zhang, Ji (Author), Gao, Qigang (Author) and Wang, Hai (Author) |
Journal or Proceedings Title | Proceedings of the 5th Dalhousie Computer Science In-house Conference (DCSI'07) |
Number of Pages | 2 |
Year | 2007 |
Place of Publication | Halifax, Nova Scotia, Canada |
Web Address (URL) of Paper | http://dcsi.cs.dal.ca/ |
Conference/Event | 5th Dalhousie Computer Science In-house Conference (DCSI'07) |
Event Details | 5th Dalhousie Computer Science In-house Conference (DCSI'07) Event Date 05 Apr 2007 Event Location Halifax, Canada |
Abstract | [Abstract]: The explosion of data streams has sparked a lot of research interests in data mining on streaming data flow in recent years. Many data streams are inherently high dimensional and outlier detection from these data streams can potentially lead to discovery of useful abnormal and irregular patterns hidden in the streams. Outlier detection in data streams can be useful in many fields such as analysis and monitoring of network |
Keywords | data mining; outlier detection; data streams |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
Public Notes | No evidence of copyright restrictions. |
Byline Affiliations | University of Toronto, Canada |
Dalhousie University, Canada | |
Saint Mary's University, Canada |
Permalink -
https://research.usq.edu.au/item/9z296/outlier-detection-for-high-dimensional-data-streams
Download files
1848
total views494
total downloads0
views this month0
downloads this month