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 51–60 of 431 papers

TitleStatusHype
RecKG: Knowledge Graph for Recommender SystemsCode1
Sudowoodo: Contrastive Self-supervised Learning for Multi-purpose Data Integration and PreparationCode1
A machine-compiled macroevolutionary history of Phanerozoic life—0
A Comparison of Neuroelectrophysiology Databases—0
A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference—0
A Theoretical Framework for Graph-based Digital Twins for Supply Chain Management and Optimization—0
A technical review of multi-omics data integration methods: from classical statistical to deep generative approaches—0
AI-driven multi-omics integration for multi-scale predictive modeling of causal genotype-environment-phenotype relationships—0
A Threefold Review on Deep Semantic Segmentation: Efficiency-oriented, Temporal and Depth-aware design—0
A Systematic Decade Review of Trip Route Planning with Travel Time Estimation based on User Preferences and Behavior—0
Show:102550
← PrevPage 6 of 44Next →

No leaderboard results yet.