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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 211–220 of 431 papers

TitleStatusHype
NCBO Ontology Recommender 2.0: An Enhanced Approach for Biomedical Ontology Recommendation—0
Need for Design Patterns: Interoperability Issues and Modelling Challenges for Observational Data—0
NEMA: Automatic Integration of Large Network Management Databases—0
Nested Deep Learning Model Towards A Foundation Model for Brain Signal Data—0
Neural decoding from stereotactic EEG: accounting for electrode variability across subjects—0
Novel Architecture for Distributed Travel Data Integration and Service Provision Using Microservices—0
On the effects of alternative optima in context-specific metabolic model predictions—0
Ontology Based Information Integration: A Survey—0
Ontology Population using LLMs—0
Optimal Estimation of Shared Singular Subspaces across Multiple Noisy Matrices—0
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