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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 401–410 of 431 papers

TitleStatusHype
Evaluating approaches for supervised semantic labelingCode0
Bayesian Joint Matrix Decomposition for Data Integration with Heterogeneous Noise—0
A Unified Joint Matrix Factorization Framework for Data IntegrationCode0
A Vision for Health Informatics: Introducing the SKED Framework.An Extensible Architecture for Scientific Knowledge Extraction from Data—0
A Framework for Accurate Drought Forecasting System Using Semantics-Based Data Integration Middleware—0
On the effects of alternative optima in context-specific metabolic model predictions—0
Bayesian Hybrid Matrix Factorisation for Data IntegrationCode0
Multi-Kernel LS-SVM Based Bio-Clinical Data Integration: Applications to Ovarian Cancer—0
Towards multiple kernel principal component analysis for integrative analysis of tumor samples—0
Neuro-symbolic representation learning on biological knowledge graphsCode0
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