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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 91100 of 431 papers

TitleStatusHype
Evaluating Blocking Biases in Entity MatchingCode0
Gaussian Copula Models for Nonignorable Missing Data Using Auxiliary Marginal QuantilesCode0
Comparative Analysis of Multi-Omics Integration Using Advanced Graph Neural Networks for Cancer ClassificationCode0
Heter-LP: A heterogeneous label propagation algorithm and its application in drug repositioningCode0
An Empirical Meta-analysis of the Life Sciences (Linked?) Open Data on the WebCode0
Consistent and Flexible Selectivity Estimation for High-Dimensional DataCode0
Efficient Vertical Federated Learning Method for Ridge Regression of Large-Scale Samples via Least-Squares SolutionCode0
Intermediate triple table: A general architecture for virtual knowledge graphsCode0
Building Flexible, Scalable, and Machine Learning-ready Multimodal Oncology DatasetsCode0
An attention model to analyse the risk of agitation and urinary tract infections in people with dementiaCode0
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