A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-27
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
The main challenges that marine heterogeneous data integration faces are the problem of accurate schema mapping between heterogeneous data sources.
In order to improve the schema mapping efficiency and get more accurate learning results, this paper proposes a heterogeneous data schema mapping method basing on multianalyzer machine learning model.
The multianalyzer analysis the learning results comprehensively, and a fuzzy comprehensive evaluation system is introduced for output results’ evaluation and multi factor quantitative judging.
Finally, the data mapping comparison experiment on the East China Sea observing data confirms the effectiveness of the model and shows multianalyzer’s obvious improvement of mapping error rate.
American Psychological Association (APA)
Yan, Wang& Jiajin, Le& Yun, Zhang. 2014. A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1048897
Modern Language Association (MLA)
Yan, Wang…[et al.]. A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping. The Scientific World Journal No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-1048897
American Medical Association (AMA)
Yan, Wang& Jiajin, Le& Yun, Zhang. A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-1048897
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048897