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 231–240 of 431 papers

TitleStatusHype
TabulaTime: A Novel Multimodal Deep Learning Framework for Advancing Acute Coronary Syndrome Prediction through Environmental and Clinical Data Integration—0
Targeted Data Fusion for Causal Survival Analysis Under Distribution Shift—0
Targeting Underrepresented Populations in Precision Medicine: A Federated Transfer Learning Approach—0
TCKAN:A Novel Integrated Network Model for Predicting Mortality Risk in Sepsis Patients—0
Technical Report on Data Integration and Preparation—0
TemporalAugmenter: An Ensemble Recurrent Based Deep Learning Approach for Signal Classification—0
The challenge of uncertainty quantification of large language models in medicine—0
The S2 Hierarchical Discrete Global Grid as a Nexus for Data Representation, Integration, and Querying Across Geospatial Knowledge Graphs—0
Time Series Data Imputation: A Survey on Deep Learning Approaches—0
Towards a Generic Multimodal Architecture for Batch and Streaming Big Data Integration—0
Show:102550
← PrevPage 24 of 44Next →

No leaderboard results yet.