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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

Showing 7180 of 431 papers

TitleStatusHype
Mind the Data Gap: Bridging LLMs to Enterprise Data Integration0
Semantic Web: Past, Present, and FutureCode0
Learn2Mix: Training Neural Networks Using Adaptive Data IntegrationCode0
GraphSeqLM: A Unified Graph Language Framework for Omic Graph LearningCode0
Federated Learning for Coronary Artery Plaque Detection in Atherosclerosis Using IVUS Imaging: A Multi-Hospital Collaboration0
Clinical Trials Ontology Engineering with Large Language Models0
Knowledge Graphs: The Future of Data Integration and Insightful Discovery0
Demonstrating Data-to-Knowledge Pipelines for Connecting Production Sites in the World Wide Lab0
Data Integration with Fusion Searchlight: Classifying Brain States from Resting-state fMRICode0
Advancements in Machine Learning and Deep Learning for Early Detection and Management of Mental Health Disorder0
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