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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 341–350 of 431 papers

TitleStatusHype
Linear Regression Evaluation of Search Engine Automatic Search Performance Based on Hadoop and R—0
Learning to Characterize Matching ExpertsCode0
A High Precision Pipeline for Financial Knowledge Graph Construction—0
Patient similarity: methods and applications—0
Time Series Data Imputation: A Survey on Deep Learning Approaches—0
DANAE: a denoising autoencoder for underwater attitude estimationCode0
COMO: A Pipeline for Multi-Omics Data Integration in Metabolic Modeling and Drug DiscoveryCode1
GripNet: Graph Information Propagation on Supergraph for Heterogeneous GraphsCode1
Diagnostic data integration using deep neural networks for real-time plasma analysis—0
Efficient Joinable Table Discovery in Data Lakes: A High-Dimensional Similarity-Based Approach—0
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