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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 391–400 of 431 papers

TitleStatusHype
Designing and Implementing Data Warehouse for Agricultural Big Data—0
Feature Selection for Data Integration with Mixed Multi-view Data—0
Scalable Similarity Joins of Tokenized Strings—0
Hybrid Modelling in Oncology: Sucesses, Challenges and Hopes—0
TweetsKB: A Public and Large-Scale RDF Corpus of Annotated Tweets—0
Reuse and Adaptation for Entity Resolution through Transfer Learning—0
Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities—0
Specifying, Monitoring, and Executing Workflows in Linked Data Environments—0
K-shell decomposition reveals hierarchical cortical organization of the human brain—0
Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical ModelsCode0
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