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Ontology-based data integration for supporting big bridge data analytics
Kaijian Liu
,
Nora El-Gohary
Civil and Environmental Engineering
National Center for Supercomputing Applications (NCSA)
Research output
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Chapter in Book/Report/Conference proceeding
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Conference contribution
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Dive into the research topics of 'Ontology-based data integration for supporting big bridge data analytics'. Together they form a unique fingerprint.
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Keyphrases
Data Analytics
100%
Ontology Integration
100%
Bridge Data
100%
Data Linking
80%
Ontology-based
60%
Proposed Methodology
20%
Learning Value
20%
Integration Method
20%
Data Integration
20%
No-Match
20%
Attribute Value
20%
Ontology
20%
Part-of
20%
Complex Interactions
20%
Machine Learning Algorithms
20%
Supertype
20%
Natural Hazards
20%
Managing Conflict
20%
Bridge Deterioration
20%
Multi-class Classification
20%
Comparison Function
20%
Data Classification
20%
Climate Risk
20%
Weather Hazards
20%
Bridge Elements
20%
Heterogeneous Format
20%
Bridge Deterioration Prediction
20%
Traffic Hazard
20%
Deterioration Factor
20%
Integration Methodology
20%
National Bridge Inventory
20%
Bridge Inspection Reports
20%
Computer Science
Data Analytics
100%
Ontology
100%
Data Integration
100%
Linking Data
66%
Experimental Result
33%
Linked Data
33%
Research Effort
16%
Data Fusion
16%
Classification Problem
16%
Attribute Value
16%
Machine Learning Algorithm
16%
Multiclass Classification
16%
Multi Class Classification
16%
Data Hazard
16%
Weather Condition
16%
Engineering
Experimental Result
100%
Data Link
100%
Similarities
50%
Integration Method
50%
Classification Problem
50%
Element Data
50%
Machine Learning Algorithm
50%
Multiclass Classification
50%
Bridge Element
50%
Physics
Data Link
100%
Machine Learning
50%
Multisensor Fusion
50%