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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 281290 of 431 papers

TitleStatusHype
Analytical Engines With Context-Rich Processing: Towards Efficient Next-Generation Analytics0
Accu-Help: A Machine Learning based Smart Healthcare Framework for Accurate Detection of Obsessive Compulsive Disorder0
Segment-based fusion of multi-sensor multi-scale satellite soil moisture retrievals0
Graph Neural Networks for Breast Cancer Data Integration0
OPTION: OPTImization Algorithm Benchmarking ONtology0
Privacy-preserving Deep Learning based Record Linkage0
Lipschitz-regularized gradient flows and generative particle algorithms for high-dimensional scarce dataCode0
Efficient Vertical Federated Learning Method for Ridge Regression of Large-Scale Samples via Least-Squares SolutionCode0
Bottom-up data integration in polymer models of chromatin organisation0
Question Answering Over Biological Knowledge Graph via Amazon Alexa0
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