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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 171–180 of 431 papers

TitleStatusHype
Multi-faceted Neuroimaging Data Integration via Analysis of Subspaces—0
Prompt-Matcher: Leveraging Large Models to Reduce Uncertainty in Schema Matching Results—0
EUR-USD Exchange Rate Forecasting Based on Information Fusion with Large Language Models and Deep Learning Methods—0
Cross-Species Data Integration for Enhanced Layer Segmentation in Kidney PathologyCode0
EraW-Net: Enhance-Refine-Align W-Net for Scene-Associated Driver Attention Estimation—0
Personalized graph feature-based multi-omics data integration for cancer subtype identification—0
MMREC: LLM Based Multi-Modal Recommender System—0
Enhancing Medical Learning and Reasoning Systems: A Boxology-Based Comparative Analysis of Design Patterns—0
VITAL: Interactive Few-Shot Imitation Learning via Visual Human-in-the-Loop Corrections—0
Intelligent Cross-Organizational Process Mining: A Survey and New Perspectives—0
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