Title :
An extensible service oriented distributed data mining framework
Author :
Kumar, Ajit ; Kantardzic, Mehmed ; Ramaswamy, P. ; Sadeghian, P.
Abstract :
This paper discusses a new approach for developing a service-oriented infrastructure for distributed data mining applications. The proposed architecture hides the complexity of implementation details and enables users to perform data mining in a utility-like fashion. The service-oriented architecture provides an autonomic data mining framework where selfdescribing data mining services can be automatically discovered on the Internet. Moreover, this structure allows for the implementation of data mining algorithms for processing data on more than one site in a distributed manner. The performance of the proposed distributed data mining framework is compared to a standard data mining approach to demonstrate its effectiveness.
Keywords :
Application software; Computer architecture; Computer science; Data engineering; Data mining; Distributed decision making; Inference algorithms; Service oriented architecture; Web and internet services; Web services;
Conference_Titel :
Machine Learning and Applications, 2004. Proceedings. 2004 International Conference on
Conference_Location :
Louisville, Kentucky, USA
Print_ISBN :
0-7803-8823-2
DOI :
10.1109/ICMLA.2004.1383522