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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 101–110 of 431 papers

TitleStatusHype
Assessing the Reproducibility of Machine-learning-based Biomarker Discovery in Parkinson's Disease—0
Control of Renewable Energy Communities using AI and Real-World Data—0
Corynebacterium glutamicum regulation beyond transcription: Organizing principles and reconstruction of an extended regulatory network incorporating regulations mediated by small RNA and protein-protein interactions—0
Prompt-Matcher: Leveraging Large Models to Reduce Uncertainty in Schema Matching Results—0
An Overview of Healthcare Data Analytics With Applications to the COVID-19 Pandemic—0
CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis—0
Crop Knowledge Discovery Based on Agricultural Big Data Integration—0
Cross-Asset Risk Management: Integrating LLMs for Real-Time Monitoring of Equity, Fixed Income, and Currency Markets—0
Advancements in Machine Learning and Deep Learning for Early Detection and Management of Mental Health Disorder—0
CDE-Mapper: Using Retrieval-Augmented Language Models for Linking Clinical Data Elements to Controlled Vocabularies—0
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