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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 191–200 of 431 papers

TitleStatusHype
Moment-based parameter inference with error guarantees for stochastic reaction networksCode0
Data Issues in Industrial AI System: A Meta-Review and Research Strategy—0
IoT-Based Preventive Mental Health Using Knowledge Graphs and Standards for Better Well-Being—0
Cluster Quilting: Spectral Clustering for Patchwork Learning—0
A Survey of Pipeline Tools for Data EngineeringCode0
Embedding-based Multimodal Learning on Pan-Squamous Cell Carcinomas for Improved Survival Outcomes—0
Multimodal Contextualized Semantic Parsing from SpeechCode0
Gaussian Copula Models for Nonignorable Missing Data Using Auxiliary Marginal QuantilesCode0
Combining Experimental and Historical Data for Policy EvaluationCode0
Leveraging Large Language Models for Entity Matching—0
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