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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

Showing 271280 of 431 papers

TitleStatusHype
Scalable Randomized Kernel Methods for Multiview Data Integration and PredictionCode0
Assessing the Reproducibility of Machine-learning-based Biomarker Discovery in Parkinson's Disease0
Multimodal Data Integration for Oncology in the Era of Deep Neural Networks: A Review0
Mining the contribution of intensive care clinical course to outcome after traumatic brain injuryCode0
A Threefold Review on Deep Semantic Segmentation: Efficiency-oriented, Temporal and Depth-aware design0
GeoFault: A well-founded fault ontology for interoperability in geological modeling0
A Biomedical Knowledge Graph for Biomarker Discovery in Cancer0
Dynamic Basis Function Interpolation for Adaptive In Situ Data Integration in Ocean Modeling0
SOTAB: The WDC Schema.org Table Annotation BenchmarkCode0
Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Genomic Data0
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