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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
DREIFLUSS: A Minimalist Approach for Table Matching—0
Knowledge Graph Representations to enhance Intensive Care Time-Series Predictions—0
Multimodal Machine Learning in Image-Based and Clinical Biomedicine: Survey and Prospects—0
Semantic Data Management in Data Lakes—0
Bi-Encoders based Species Normalization -- Pairwise Sentence Learning to Rank—0
Transformer-based Entity Legal Form ClassificationCode1
Uncertainty in Automated Ontology Matching: Lessons Learned from an Empirical Experimentation—0
Entity Matching using Large Language ModelsCode1
Graph Neural Network approaches for single-cell data: A recent overview—0
Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics—0
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