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 311–320 of 431 papers

TitleStatusHype
Proceedings 37th International Conference on Logic Programming (Technical Communications)—0
PoWareMatch: a Quality-aware Deep Learning Approach to Improve Human Schema MatchingCode0
Making Table Understanding Work in Practice—0
Integrated community occupancy models: A framework to assess occurrence and biodiversity dynamics using multiple data sourcesCode0
Targeting Underrepresented Populations in Precision Medicine: A Federated Transfer Learning Approach—0
Towards a Generic Multimodal Architecture for Batch and Streaming Big Data Integration—0
Data Integration for Toxic Comment Classification: Making More Than 40 Datasets Easily Accessible in One Unified FormatCode1
Parallelisable Existential Rules: a Story of Pieces—0
Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and FairnessCode1
Computer-Assisted Analysis of Biomedical Images—0
Show:102550
← PrevPage 32 of 44Next →

No leaderboard results yet.