A Novel Data Mining Platform Design with Dynamic Algorithm Base
- Hebiao Yang
- Yukun Chen
- Rengang Hou
Abstract
With the application domain of data mining technologies extends increasingly, some shortages of the commonly used commercial data mining tools, such as poor maintainability, less expansibility and high cost, are gradually exposed in practice. As such, these tools cannot flexibly and effectively meet the apt-to-change demands of users. This paper proposes a plugin style method for dynamic algorithm base design, discusses issues related to the joint between data set and mining algorithms and implements the platform prototype, providing a frame reference for constructing a wieldy, usable, extensible and low cost data mining platform.
- Full Text: PDF
- DOI:10.5539/cis.v2n2p98
Journal Metrics
WJCI (2022): 0.636
Impact Factor 2022 (by WJCI): 0.419
h-index (January 2024): 43
i10-index (January 2024): 193
h5-index (January 2024): N/A
h5-median(January 2024): N/A
( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )
Index
- Academic Journals Database
- BASE (Bielefeld Academic Search Engine)
- CiteFactor
- CNKI Scholar
- COPAC
- CrossRef
- DBLP (2008-2019)
- EBSCOhost
- EuroPub Database
- Excellence in Research for Australia (ERA)
- Genamics JournalSeek
- Google Scholar
- Harvard Library
- Infotrieve
- LOCKSS
- Mendeley
- PKP Open Archives Harvester
- Publons
- ResearchGate
- Scilit
- SHERPA/RoMEO
- Standard Periodical Directory
- The Index of Information Systems Journals
- The Keepers Registry
- UCR Library
- Universe Digital Library
- WJCI Report
- WorldCat
Contact
- Chris LeeEditorial Assistant
- cis@ccsenet.org