A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping
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...
Saved in:
Main Authors: | Wang Yan, Le Jiajin, Zhang Yun |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2014-01-01
|
Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2014/248467 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Semi-automatic construction of heterogeneous data schema based on structure and context-aware recommendation
by: Nan Yin, et al.
Published: (2025-02-01) -
Developing an Extended IFC Data Schema and Mesh Generation Framework for Finite Element Modeling
by: Zhao Xu, et al.
Published: (2019-01-01) -
Learning transitivity schemas: The role of the number of nominals and word order
by: Audisio Cynthia Pamela
Published: (2024-01-01) -
Robust Automated Harmonization of Heterogeneous Data Through Ensemble Machine Learning: Algorithm Development and Validation Study
by: Doris Yang, et al.
Published: (2025-01-01) -
Potential for Vertical Heterogeneity Prediction in Reservoir Basing on Machine Learning Methods
by: Hongqing Song, et al.
Published: (2020-01-01)