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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 261–270 of 431 papers

TitleStatusHype
Skeleton Detection Using Dual Radars with Integration of Dual-View CNN Models and mmPose—0
Smart City Digital Twin Framework for Real-Time Multi-Data Integration and Wide Public Distribution—0
Specifying, Monitoring, and Executing Workflows in Linked Data Environments—0
Statistical Agnostic Regression: a machine learning method to validate regression models—0
Stochastic Biological System-of-Systems Modelling for iPSC Culture—0
Stratified Data Integration—0
Streamlining Knowledge Graph Creation with PyRML—0
Structured Matrix Completion with Applications to Genomic Data Integration—0
Supervised prediction of aging-related genes from a context-specific protein interaction subnetwork—0
Survive the Schema Changes: Integration of Unmanaged Data Using Deep Learning—0
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