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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 101–125 of 431 papers

TitleStatusHype
Intermediate triple table: A general architecture for virtual knowledge graphsCode0
Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models—0
Integrating Weather Station Data and Radar for Precipitation Nowcasting: SmaAt-fUsion and SmaAt-Krige-GNetCode0
Cross-Format Retrieval-Augmented Generation in XR with LLMs for Context-Aware Maintenance Assistance—0
Advancing Precision Oncology Through Modeling of Longitudinal and Multimodal Data—0
LLMs in Software Security: A Survey of Vulnerability Detection Techniques and InsightsCode0
Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation—0
Ilargi: a GPU Compatible Factorized ML Model Training Framework—0
Common Foundations for SHACL, ShEx, and PG-Schema—0
Targeted Data Fusion for Causal Survival Analysis Under Distribution Shift—0
A technical review of multi-omics data integration methods: from classical statistical to deep generative approaches—0
PulmoFusion: Advancing Pulmonary Health with Efficient Multi-Modal FusionCode0
Fuzzy Integration of Data Lake Tables—0
Transforming Social Science Research with Transfer Learning: Social Science Survey Data Integration with AI—0
Graph-based Retrieval Augmented Generation for Dynamic Few-shot Text Classification—0
IAM: Enhancing RGB-D Instance Segmentation with New BenchmarksCode0
Real-time Cross-modal Cybersickness Prediction in Virtual Reality—0
Mind the Data Gap: Bridging LLMs to Enterprise Data Integration—0
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 Collaboration—0
Clinical Trials Ontology Engineering with Large Language Models—0
Knowledge Graphs: The Future of Data Integration and Insightful Discovery—0
Demonstrating Data-to-Knowledge Pipelines for Connecting Production Sites in the World Wide Lab—0
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