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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 231240 of 431 papers

TitleStatusHype
Towards a Microservice-based Middleware for a Multi-hazard Early Warning System0
A deep learning pipeline for cross-sectional and longitudinal multiview data integrationCode0
Knowledge Graph Reasoning Based on Attention GCN0
The Battleship Approach to the Low Resource Entity Matching ProblemCode0
Exploring Artificial Intelligence Methods for Energy Prediction in Healthcare Facilities: An In-Depth Extended Systematic Review0
mvlearnR and Shiny App for multiview learningCode0
Deep Learning and NLP in Cryptocurrency Forecasting: Integrating Financial, Blockchain, and Social Media Data0
Regression-Based Analysis of Multimodal Single-Cell Data Integration Strategies0
DREIFLUSS: A Minimalist Approach for Table Matching0
Knowledge Graph Representations to enhance Intensive Care Time-Series Predictions0
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