DocumentCode
1957680
Title
The Anatomy of Weka4WS: A WSRF-enabled Toolkit for Distributed Data Mining on Grid
Author
Zheng, Zhao ; Shu, Gao
Author_Institution
Sch. of Comput. Sci., Wuhan Univ. of Technol., Wuhan
Volume
3
fYear
2008
fDate
12-14 Dec. 2008
Firstpage
53
Lastpage
57
Abstract
Data mining technology is widely used for the analysis of large datasets stored in databases. However, conventional data mining is not satisfied with the requirement due to the heterogeneous and distributed of the datasets. Grid computing emerged as an important new field of distributed computing, which could support for distributed knowledge discovery applications. Weka4WS is an open-source framework extended from the Weka toolkit for distributed data mining on Grid, which deploys many of machine learning algorithms provided by Weka Toolkit as WSRF-compliant services. This paper presents the architecture, implementation and execution of Weka4WS. At last, an example about distributed Classification is given to illustrate the effective of Weka4WS framework further.
Keywords
data mining; grid computing; WSRF-compliant services; Weka toolkit; Weka4WS; datasets; distributed data mining; distributed knowledge discovery applications; grid computing; Anatomy; Computer architecture; Computer science; Data mining; Delta modulation; Distributed computing; Grid computing; Machine learning algorithms; Resource management; Web services; GT4; Mammography; Weka; Weka4WS;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-0-7695-3336-0
Type
conf
DOI
10.1109/CSSE.2008.629
Filename
4722288
Link To Document