SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 321–330 of 431 papers

TitleStatusHype
Dual-Objective Fine-Tuning of BERT for Entity MatchingCode1
Modeling multi-scale data via a network of networks—0
Dynamical models for metabolomics data integration—0
Stratified Data Integration—0
Business Entity Matching with Siamese Graph Convolutional Networks—0
Federated Multi-View Learning for Private Medical Data Integration and Analysis—0
Integration of Unpaired Single-cell Chromatin Accessibility and Gene Expression Data via Adversarial Learning—0
OPTION: OPTImization Algorithm Benchmarking ONtology—0
Large Scale Record Linkage in the Presence of Missing Data—0
Orthogonalized Kernel Debiased Machine Learning for Multimodal Data Analysis—0
Show:102550
← PrevPage 33 of 44Next →

No leaderboard results yet.