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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 271–280 of 431 papers

TitleStatusHype
Graph Neural Networks for Breast Cancer Data Integration—0
OPTION: OPTImization Algorithm Benchmarking ONtology—0
Privacy-preserving Deep Learning based Record Linkage—0
Lipschitz-regularized gradient flows and generative particle algorithms for high-dimensional scarce dataCode0
Efficient Vertical Federated Learning Method for Ridge Regression of Large-Scale Samples via Least-Squares SolutionCode0
Bottom-up data integration in polymer models of chromatin organisation—0
Question Answering Over Biological Knowledge Graph via Amazon Alexa—0
An Ontology for Defect Detection in Metal Additive Manufacturing—0
Popularity Driven Data Integration—0
Query-based Industrial Analytics over Knowledge Graphs with Ontology Reshaping—0
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