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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 251260 of 431 papers

TitleStatusHype
Inferring High-level Geographical Concepts via Knowledge Graph and Multi-scale Data Integration: A Case Study of C-shaped Building Pattern Recognition0
CLCLSA: Cross-omics Linked embedding with Contrastive Learning and Self Attention for multi-omics integration with incomplete multi-omics data0
Learnings from Data Integration for Augmented Language Models0
Scalable Randomized Kernel Methods for Multiview Data Integration and PredictionCode0
Assessing the Reproducibility of Machine-learning-based Biomarker Discovery in Parkinson's Disease0
Multimodal Data Integration for Oncology in the Era of Deep Neural Networks: A Review0
Mining the contribution of intensive care clinical course to outcome after traumatic brain injuryCode0
A Threefold Review on Deep Semantic Segmentation: Efficiency-oriented, Temporal and Depth-aware design0
Web-Scale Academic Name Disambiguation: the WhoIsWho Benchmark, Leaderboard, and ToolkitCode1
GeoFault: A well-founded fault ontology for interoperability in geological modeling0
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