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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 231–240 of 431 papers

TitleStatusHype
Personalized graph feature-based multi-omics data integration for cancer subtype identification—0
Petri Nets with Parameterised Data: Modelling and Verification (Extended Version)—0
Popularity Driven Data Integration—0
Predicting Cardiopulmonary Exercise Testing Outcomes in Congenital Heart Disease Through Multi-modal Data Integration and Geometric Learning—0
Principled Graph Matching Algorithms for Integrating Multiple Data Sources—0
Privacy-preserving Deep Learning based Record Linkage—0
Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data—0
Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models—0
Proceedings 35th International Conference on Logic Programming (Technical Communications)—0
Proceedings 36th International Conference on Logic Programming (Technical Communications)—0
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