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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 301–310 of 431 papers

TitleStatusHype
K-shell decomposition reveals hierarchical cortical organization of the human brain—0
Large Scale Record Linkage in the Presence of Missing Data—0
LEAPME: Learning-based Property Matching with Embeddings—0
Learnings from Data Integration for Augmented Language Models—0
Leveraging Language Models for Automated Patient Record Linkage—0
Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directions—0
Leveraging Large Language Models for Entity Matching—0
Leveraging MIMIC Datasets for Better Digital Health: A Review on Open Problems, Progress Highlights, and Future Promises—0
Linear Regression Evaluation of Search Engine Automatic Search Performance Based on Hadoop and R—0
Linking Graph Entities with Multiplicity and Provenance—0
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