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Data Integration

Data integration (also called information integration) is the process of consolidating data from a set of heterogeneous data sources into a single uniform data set (materialized integration) or view on the data (virtual integration). Data integration pipelines involve subtasks such as schema matching, table annotation, entity resolution, value normalization, data cleansing, and data fusion. Application domains of data integration include data warehousing, data lakes, and knowledge base consolidation. Surveys on Data integration:

Papers

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Showing 61–70 of 431 papers

TitleStatusHype
A machine-compiled macroevolutionary history of Phanerozoic life—0
Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey—0
A Systematic Decade Review of Trip Route Planning with Travel Time Estimation based on User Preferences and Behavior—0
A High Precision Pipeline for Financial Knowledge Graph Construction—0
Reasoning about disclosure in data integration in the presence of source constraints—0
Can Large Language Models Unveil the Mysteries? An Exploration of Their Ability to Unlock Information in Complex Scenarios—0
A survey on deep learning approaches for data integration in autonomous driving system—0
A health telemonitoring platform based on data integration from different sources—0
A Circular Construction Product Ontology for End-of-Life Decision-Making—0
A Survey of Data Quality Measurement and Monitoring Tools—0
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