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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 51–60 of 431 papers

TitleStatusHype
Intermediate triple table: A general architecture for virtual knowledge graphsCode0
TabulaTime: A Novel Multimodal Deep Learning Framework for Advancing Acute Coronary Syndrome Prediction through Environmental and Clinical Data Integration—0
Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models—0
Integrating Weather Station Data and Radar for Precipitation Nowcasting: SmaAt-fUsion and SmaAt-Krige-GNetCode0
Cross-Format Retrieval-Augmented Generation in XR with LLMs for Context-Aware Maintenance Assistance—0
Advancing Precision Oncology Through Modeling of Longitudinal and Multimodal Data—0
LLMs in Software Security: A Survey of Vulnerability Detection Techniques and InsightsCode0
Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation—0
Ilargi: a GPU Compatible Factorized ML Model Training Framework—0
Common Foundations for SHACL, ShEx, and PG-Schema—0
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