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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 411–420 of 431 papers

TitleStatusHype
Data Integration with Fusion Searchlight: Classifying Brain States from Resting-state fMRICode0
Supervised Multiple Kernel Learning approaches for multi-omics data integrationCode0
Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical ModelsCode0
The scalable Birth-Death MCMC Algorithm for Mixed Graphical Model Learning with Application to Genomic Data IntegrationCode0
Kernel learning approaches for summarising and combining posterior similarity matricesCode0
DANAE: a denoising autoencoder for underwater attitude estimationCode0
A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep LearningCode0
Weakly-Supervised Multimodal Learning on MIMIC-CXRCode0
PoWareMatch: a Quality-aware Deep Learning Approach to Improve Human Schema MatchingCode0
Multimodal Quantum Natural Language Processing: A Novel Framework for using Quantum Methods to Analyse Real DataCode0
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