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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 31–40 of 431 papers

TitleStatusHype
The challenge of uncertainty quantification of large language models in medicine—0
OmniEcon Nexus: Global Microeconomic Simulation EngineCode0
From Automation to Autonomy in Smart Manufacturing: A Bayesian Optimization Framework for Modeling Multi-Objective Experimentation and Sequential Decision Making—0
Cross-Asset Risk Management: Integrating LLMs for Real-Time Monitoring of Equity, Fixed Income, and Currency Markets—0
A Systematic Decade Review of Trip Route Planning with Travel Time Estimation based on User Preferences and Behavior—0
Multimodal Data Integration for Sustainable Indoor Gardening: Tracking Anyplant with Time Series Foundation Model—0
Multi-dataset and Transfer Learning Using Gene Expression Knowledge GraphsCode0
Federated Learning: A new frontier in the exploration of multi-institutional medical imaging data—0
GridMind: A Multi-Agent NLP Framework for Unified, Cross-Modal NFL Data Insights—0
MODIS: Multi-Omics Data Integration for Small and Unpaired DatasetsCode0
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