Back to Search Start Over

A Survey of Open Source Data Mining Systems.

Authors :
Carbonell, Jaime G.
Siekmann, Jörg
Washio, Takashi
Zhi-Hua Zhou
Joshua Zhexue Huang
Xiaohua Hu
Jinyan Li
Chao Xie
Jieyue He
Deqing Zou
Kuan-Ching Li
Freire, Mário M.
Xiaojun Chen
Yunming Ye
Williams, Graham
Xiaofei Xu
Source :
Emerging Technologies in Knowledge Discovery & Data Mining; 2007, p3-14, 12p
Publication Year :
2007

Abstract

Open source data mining software represents a new trend in data mining research, education and industrial applications, especially in small and medium enterprises (SMEs). With open source software an enterprise can easily initiate a data mining project using the most current technology. Often the software is available at no cost, allowing the enterprise to instead focus on ensuring their staff can freely learn the data mining techniques and methods. Open source ensures that staff can understand exactly how the algorithms work by examining the source codes, if they so desire, and can also fine tune the algorithms to suit the specific purposes of the enterprise. However, diversity, instability, scalability and poor documentation can be major concerns in using open source data mining systems. In this paper, we survey open source data mining systems currently available on the Internet. We compare 12 open source systems against several aspects such as general characteristics, data source accessibility, data mining functionality, and usability. We discuss advantages and disadvantages of these open source data mining systems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540770169
Database :
Complementary Index
Journal :
Emerging Technologies in Knowledge Discovery & Data Mining
Publication Type :
Book
Accession number :
33751856
Full Text :
https://doi.org/10.1007/978-3-540-77018-3_2