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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 181190 of 431 papers

TitleStatusHype
iMD4GC: Incomplete Multimodal Data Integration to Advance Precise Treatment Response Prediction and Survival Analysis for Gastric CancerCode1
Supervised Multiple Kernel Learning approaches for multi-omics data integrationCode0
Disambiguate Entity Matching using Large Language Models through Relation Discovery0
Declarative generation of RDF-star graphs from heterogeneous dataCode3
Advancing Explainable Autonomous Vehicle Systems: A Comprehensive Review and Research Roadmap0
A2CI: A Cloud-based, Service-oriented Geospatial Cyberinfrastructure to Support Atmospheric Research0
Developing and Deploying Industry Standards for Artificial Intelligence in Education (AIED): Challenges, Strategies, and Future Directions0
Data augmentation with automated machine learning: approaches and performance comparison with classical data augmentation methods0
ReMatch: Retrieval Enhanced Schema Matching with LLMsCode0
preon: Fast and accurate entity normalization for drug names and cancer types in precision oncologyCode0
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