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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 41–50 of 431 papers

TitleStatusHype
Integrating Multimodal Data for Joint Generative Modeling of Complex DynamicsCode1
Sudowoodo: Contrastive Self-supervised Learning for Multi-purpose Data Integration and PreparationCode1
Domain Adaptation for Deep Entity Resolution: A Design Space ExplorationCode1
Cross-Domain Data Integration for Named Entity Disambiguation in Biomedical TextCode1
Data Integration for Toxic Comment Classification: Making More Than 40 Datasets Easily Accessible in One Unified FormatCode1
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and FairnessCode1
Dual-Objective Fine-Tuning of BERT for Entity MatchingCode1
A Variational Information Bottleneck Approach to Multi-Omics Data IntegrationCode1
COMO: A Pipeline for Multi-Omics Data Integration in Metabolic Modeling and Drug DiscoveryCode1
GripNet: Graph Information Propagation on Supergraph for Heterogeneous GraphsCode1
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