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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

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Showing 161–170 of 431 papers

TitleStatusHype
Prompt-Matcher: Leveraging Large Models to Reduce Uncertainty in Schema Matching Results—0
Corynebacterium glutamicum regulation beyond transcription: Organizing principles and reconstruction of an extended regulatory network incorporating regulations mediated by small RNA and protein-protein interactions—0
Assumption-Lean Post-Integrated Inference with Negative Control Outcomes—0
A Gap in Time: The Challenge of Processing Heterogeneous IoT Data in Digitalized Buildings—0
A Circular Construction Product Ontology for End-of-Life Decision-Making—0
Control of Renewable Energy Communities using AI and Real-World Data—0
Assessing the Reproducibility of Machine-learning-based Biomarker Discovery in Parkinson's Disease—0
Contrastive Entity Linkage: Mining Variational Attributes from Large Catalogs for Entity Linkage—0
A Semantic Analyzer for the Comprehension of the Spontaneous Arabic Speech—0
A Framework for Accurate Drought Forecasting System Using Semantics-Based Data Integration Middleware—0
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