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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 291–300 of 431 papers

TitleStatusHype
Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey—0
Driving Digital Engineering Integration and Interoperability Through Semantic Integration of Models with Ontologies—0
Domain Adaptation for Deep Entity Resolution: A Design Space ExplorationCode1
A review of machine learning approaches, challenges and prospects for computational tumor pathology—0
FadMan: Federated Anomaly Detection across Multiple Attributed Networks—0
Towards future directions in data-integrative supervised prediction of human aging-related genes—0
scICML: Information-theoretic Co-clustering-based Multi-view Learning for the Integrative Analysis of Single-cell Multi-omics data—0
KnowGraph-PM: a Knowledge Graph based Pricing Model for Semiconductors Supply Chains—0
Multi-Graph based Multi-Scenario Recommendation in Large-scale Online Video Services—0
Human's Role in-the-Loop—0
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