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A survey on mining multiple data sources

delete2012-11-16
delete8
PRE
AI
R
Ramkumar Thirunavukarasu *
S
Shanmugasundaram Hariharan
S
S. Selvamuthukumaran
DOI：10.1002/widm.1077delete
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Abstract

Abstract

En 中文
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.
Keywords:
HIGH-FREQUENCY RULES
ASSOCIATION RULES
DATABASES

Journal

Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery cover
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
IF:
11.7
Papers:
532
Citations:
5.3K

Organization

No organization information available