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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 141–150 of 431 papers

TitleStatusHype
Biodiversity data standards for the organization and dissemination of complex research projects and digital twins: a guide—0
An Attention-Based Multi-Context Convolutional Encoder-Decoder Neural Network for Work Zone Traffic Impact Prediction—0
Driving Digital Engineering Integration and Interoperability Through Semantic Integration of Models with Ontologies—0
DREIFLUSS: A Minimalist Approach for Table Matching—0
BIM-to-BRICK: Using graph modeling for IoT/BMS and spatial semantic data interoperability within digital data models of buildings—0
Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction—0
Drug response prediction by inferring pathway-response associations with Kernelized Bayesian Matrix Factorization—0
Bi-Encoders based Species Normalization -- Pairwise Sentence Learning to Rank—0
Analytical Engines With Context-Rich Processing: Towards Efficient Next-Generation Analytics—0
Address-Specific Sustainable Accommodation Choice Through Real-World Data Integration—0
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