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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

Showing 351360 of 431 papers

TitleStatusHype
Evaluating Blocking Biases in Entity MatchingCode0
Leveraging Legacy Data to Accelerate Materials Design via Preference LearningCode0
Semantic Web: Past, Present, and FutureCode0
Towards a Spatiotemporal Fusion Approach to Precipitation NowcastingCode0
mvlearnR and Shiny App for multiview learningCode0
Lipschitz-regularized gradient flows and generative particle algorithms for high-dimensional scarce dataCode0
Cross-Species Data Integration for Enhanced Layer Segmentation in Kidney PathologyCode0
Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration Across Distributed Data SourcesCode0
AdapterEM: Pre-trained Language Model Adaptation for Generalized Entity Matching using Adapter-tuningCode0
Bayesian Hybrid Matrix Factorisation for Data IntegrationCode0
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