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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 411–420 of 431 papers

TitleStatusHype
Empowering Cognitive Digital Twins with Generative Foundation Models: Developing a Low-Carbon Integrated Freight Transportation System—0
Empowering Digital Agriculture: A Privacy-Preserving Framework for Data Sharing and Collaborative Research—0
Enhancing Bagging Ensemble Regression with Data Integration for Time Series-Based Diabetes Prediction—0
Enhancing End Stage Renal Disease Outcome Prediction: A Multi-Sourced Data-Driven Approach—0
Enhancing Function-Calling Capabilities in LLMs: Strategies for Prompt Formats, Data Integration, and Multilingual Translation—0
Enhancing streamflow forecast and extracting insights using long-short term memory networks with data integration at continental scales—0
EquiNMF: Graph Regularized Multiview Nonnegative Matrix Factorization—0
EraW-Net: Enhance-Refine-Align W-Net for Scene-Associated Driver Attention Estimation—0
EUR-USD Exchange Rate Forecasting Based on Information Fusion with Large Language Models and Deep Learning Methods—0
Exploring Artificial Intelligence Methods for Energy Prediction in Healthcare Facilities: An In-Depth Extended Systematic Review—0
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