A survey on mining multiple data sources
Article first published online: 16 NOV 2012
Copyright © 2012 John Wiley & Sons, Inc.
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Volume 3, Issue 1, pages 1–11, January/February 2013
How to Cite
Ramkumar, T., Hariharan, S. and Selvamuthukumaran, S. (2013), A survey on mining multiple data sources. WIREs Data Mining Knowl Discov, 3: 1–11. doi: 10.1002/widm.1077
- Issue published online: 9 JAN 2013
- Article first published online: 16 NOV 2012
Advancements in computer and communication technologies demand new perceptions of distributed computing environments and development of distributed data sources for storing voluminous amount of data. In such circumstances, mining multiple data sources for extracting useful patterns of significance is being considered as a challenging task within the data mining community. The domain, multi-database mining (MDM) is regarded as a promising research area as evidenced by numerous research attempts in the recent past. The methods exist for discovering knowledge from multiple data sources, they fall into two wide categories, namely (1) mono-database mining and (2) local pattern analysis. The main intent of the survey is to explain the idea behind those approaches and consolidate the research contributions along with their significance and limitations.