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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 201–210 of 431 papers

TitleStatusHype
RDGCL: Reaction-Diffusion Graph Contrastive Learning for Recommendation—0
Towards a Microservice-based Middleware for a Multi-hazard Early Warning System—0
Cost-Effective In-Context Learning for Entity Resolution: A Design Space ExplorationCode1
Knowledge Graph Reasoning Based on Attention GCN—0
A deep learning pipeline for cross-sectional and longitudinal multiview data integrationCode0
Exploring Artificial Intelligence Methods for Energy Prediction in Healthcare Facilities: An In-Depth Extended Systematic Review—0
The Battleship Approach to the Low Resource Entity Matching ProblemCode0
mvlearnR and Shiny App for multiview learningCode0
Deep Learning and NLP in Cryptocurrency Forecasting: Integrating Financial, Blockchain, and Social Media Data—0
Regression-Based Analysis of Multimodal Single-Cell Data Integration Strategies—0
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