Mining multiple large data sources
Joint Authors
Adhikari, Jhimli
Adhikari, Animesh
Ramachandrarao, Pralhad
Prasad, Bhanu
Source
The International Arab Journal of Information Technology
Issue
Vol. 7, Issue 3 (31 Jul. 2010), pp.241-249, 9 p.
Publisher
Publication Date
2010-07-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Topics
Abstract EN
Effective data analysis using multiple databases requires highly accurate patterns.
Local pattern analysis might extract low quality patterns from multiple large databases.
Thus, it is necessary to improve mining multiple databases using local pattern analysis.
We present existing specialized as well as generalized techniques for mining multiple large databases.
We formalize the idea of multi-database mining using local pattern analysis and propose a new generalized technique for mining multiple large databases.
It improves the quality of synthesized global patterns significantly.
We conduct experiments on both real and synthetic databases to judge the effectiveness of the proposed technique.
American Psychological Association (APA)
Adhikari, Animesh& Ramachandrarao, Pralhad& Prasad, Bhanu& Adhikari, Jhimli. 2010. Mining multiple large data sources. The International Arab Journal of Information Technology،Vol. 7, no. 3, pp.241-249.
https://search.emarefa.net/detail/BIM-109220
Modern Language Association (MLA)
Ramachandrarao, Pralhad…[et al.]. Mining multiple large data sources. The International Arab Journal of Information Technology Vol. 7, no. 3 (Jul. 2010), pp.241-249.
https://search.emarefa.net/detail/BIM-109220
American Medical Association (AMA)
Adhikari, Animesh& Ramachandrarao, Pralhad& Prasad, Bhanu& Adhikari, Jhimli. Mining multiple large data sources. The International Arab Journal of Information Technology. 2010. Vol. 7, no. 3, pp.241-249.
https://search.emarefa.net/detail/BIM-109220
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 248
Record ID
BIM-109220