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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 201–210 of 431 papers

TitleStatusHype
Combining exome and gene expression datasets in one graphical model of disease to empower the discovery of disease mechanisms—0
Application of Artificial Intelligence in Schizophrenia Rehabilitation Management: A Systematic Scoping Review—0
Fast Record Linkage for Company Entities—0
Graph Neural Networks for Breast Cancer Data Integration—0
Causal Feature Selection for Algorithmic Fairness—0
FadMan: Federated Anomaly Detection across Multiple Attributed Networks—0
GridMind: A Multi-Agent NLP Framework for Unified, Cross-Modal NFL Data Insights—0
Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmap—0
Acceleration of Deep Neural Network Training with Resistive Cross-Point Devices—0
Exploring LLM Agents for Cleaning Tabular Machine Learning Datasets—0
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