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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 391–400 of 431 papers

TitleStatusHype
IAM: Enhancing RGB-D Instance Segmentation with New BenchmarksCode0
Reconstructing Nonlinear Dynamical Systems from Multi-Modal Time SeriesCode0
Multi-dataset and Transfer Learning Using Gene Expression Knowledge GraphsCode0
Elastic Coupled Co-clustering for Single-Cell Genomic DataCode0
The Battleship Approach to the Low Resource Entity Matching ProblemCode0
The Cell Ontology in the age of single-cell omicsCode0
Combining Experimental and Historical Data for Policy EvaluationCode0
Efficient Vertical Federated Learning Method for Ridge Regression of Large-Scale Samples via Least-Squares SolutionCode0
Integrated community occupancy models: A framework to assess occurrence and biodiversity dynamics using multiple data sourcesCode0
Integrating Heterogeneous Gene Expression Data through Knowledge Graphs for Improving Diabetes PredictionCode0
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