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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 71–80 of 431 papers

TitleStatusHype
A Gap in Time: The Challenge of Processing Heterogeneous IoT Data in Digitalized Buildings—0
Accu-Help: A Machine Learning based Smart Healthcare Framework for Accurate Detection of Obsessive Compulsive Disorder—0
Assessing the Reproducibility of Machine-learning-based Biomarker Discovery in Parkinson's Disease—0
A Semantic Analyzer for the Comprehension of the Spontaneous Arabic Speech—0
A Framework for Accurate Drought Forecasting System Using Semantics-Based Data Integration Middleware—0
A robust kernel machine regression towards biomarker selection in multi-omics datasets of osteoporosis for drug discovery—0
A review of machine learning approaches, challenges and prospects for computational tumor pathology—0
Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques—0
Common Foundations for SHACL, ShEx, and PG-Schema—0
A Pseudo-Likelihood Approach to Linear Regression with Partially Shuffled Data—0
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