DocumentCode
3618188
Title
Online mining of data streams: applications, techniques and progress
Author
H. Wang;J. Pei;P.S. Yu
Author_Institution
IBM Thomas J. Watson Res. Center, NY, USA
fYear
2005
fDate
6/27/1905 12:00:00 AM
Firstpage
1146
Abstract
In this paper, we focus on the differences between mining static large data sets and data streams. Over the years, the database and data mining community have learned valuable lessons from mining static large data sets, and developed many useful algorithms and tools for this purpose. The paper aims at providing a shortcut to the current frontier of stream mining research. We emphasize the research problems, the inherent technical challenges and the latest results. Particularly, the paper highlights new challenges and potential research interests. Research community has been interested in the integration between data mining tasks and database management systems.
Keywords
"Data mining","Seminars","Roads","Stock markets","Intrusion detection","Database systems","Aggregates","Frequency","Data engineering"
Publisher
ieee
Conference_Titel
Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on
ISSN
1084-4627
Print_ISBN
0-7695-2285-8
Type
conf
DOI
10.1109/ICDE.2005.101
Filename
1410243
Link To Document