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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 301–310 of 431 papers

TitleStatusHype
RadioPathomics: Multimodal Learning in Non-Small Cell Lung Cancer for Adaptive Radiotherapy—0
It's AI Match: A Two-Step Approach for Schema Matching Using Embeddings—0
Graph Neural Networks for Multimodal Single-Cell Data IntegrationCode2
A robust kernel machine regression towards biomarker selection in multi-omics datasets of osteoporosis for drug discovery—0
Easy Semantification of Bioassays—0
An Overview of Healthcare Data Analytics With Applications to the COVID-19 Pandemic—0
A big data intelligence marketplace and secure analytics experimentation platform for the aviation industry—0
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time SeriesCode0
High-resolution rainfall-runoff modeling using graph neural network—0
Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical TextCode1
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