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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 8190 of 431 papers

TitleStatusHype
Evaluating AI capabilities in detecting conspiracy theories on YouTubeCode0
Evaluating Blocking Biases in Entity MatchingCode0
Enhancing Glucose Level Prediction of ICU Patients through Hierarchical Modeling of Irregular Time-SeriesCode0
CAVACHON: a hierarchical variational autoencoder to integrate multi-modal single-cell dataCode0
Elastic Coupled Co-clustering for Single-Cell Genomic DataCode0
Entropic Optimal Transport Eigenmaps for Nonlinear Alignment and Joint Embedding of High-Dimensional DatasetsCode0
From Classical Machine Learning to Emerging Foundation Models: Review on Multimodal Data Integration for Cancer ResearchCode0
GraphSeqLM: A Unified Graph Language Framework for Omic Graph LearningCode0
An Empirical Meta-analysis of the Life Sciences (Linked?) Open Data on the WebCode0
Building Flexible, Scalable, and Machine Learning-ready Multimodal Oncology DatasetsCode0
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