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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 181–190 of 431 papers

TitleStatusHype
Federated Learning for Coronary Artery Plaque Detection in Atherosclerosis Using IVUS Imaging: A Multi-Hospital Collaboration—0
Application of Artificial Intelligence in Schizophrenia Rehabilitation Management: A Systematic Scoping Review—0
Federated Learning over Harmonized Data Silos—0
Federated Multi-View Learning for Private Medical Data Integration and Analysis—0
Diffusion Transport Alignment—0
Deep Learning and NLP in Cryptocurrency Forecasting: Integrating Financial, Blockchain, and Social Media Data—0
From Automation to Autonomy in Smart Manufacturing: A Bayesian Optimization Framework for Modeling Multi-Objective Experimentation and Sequential Decision Making—0
A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data—0
Beyond designer's knowledge: Generating materials design hypotheses via large language models—0
Analyses and Concerns in Precision Medicine: A Statistical Perspective—0
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