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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

Showing 361370 of 431 papers

TitleStatusHype
Community-Based Data Integration of Course and Job Data in Support of Personalized Career-Education Recommendations0
DINGO: an ontology for projects and grants linked data0
Petri Nets with Parameterised Data: Modelling and Verification (Extended Version)0
Causal Feature Selection for Algorithmic Fairness0
An Empirical Meta-analysis of the Life Sciences (Linked?) Open Data on the WebCode0
NEMA: Automatic Integration of Large Network Management Databases0
Secure and Differentially Private Bayesian Learning on Distributed Data0
Consistent and Flexible Selectivity Estimation for High-Dimensional DataCode0
The scalable Birth-Death MCMC Algorithm for Mixed Graphical Model Learning with Application to Genomic Data IntegrationCode0
A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep LearningCode0
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