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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 41–50 of 431 papers

TitleStatusHype
A Theoretical Framework for Graph-based Digital Twins for Supply Chain Management and Optimization—0
Predicting Cardiopulmonary Exercise Testing Outcomes in Congenital Heart Disease Through Multi-modal Data Integration and Geometric Learning—0
FusDreamer: Label-efficient Remote Sensing World Model for Multimodal Data ClassificationCode1
A Circular Construction Product Ontology for End-of-Life Decision-Making—0
RetSTA: An LLM-Based Approach for Standardizing Clinical Fundus Image ReportsCode0
Representation Retrieval Learning for Heterogeneous Data Integration—0
Hierarchical Cross-Modal Alignment for Open-Vocabulary 3D Object Detection—0
Exploring LLM Agents for Cleaning Tabular Machine Learning Datasets—0
Systematic Literature Review on Clinical Trial Eligibility Matching—0
Can Large Language Models Unveil the Mysteries? An Exploration of Their Ability to Unlock Information in Complex Scenarios—0
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