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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 401–410 of 431 papers

TitleStatusHype
Disambiguate Entity Matching using Large Language Models through Relation Discovery—0
Document Parsing Unveiled: Techniques, Challenges, and Prospects for Structured Information Extraction—0
DREIFLUSS: A Minimalist Approach for Table Matching—0
Driving Digital Engineering Integration and Interoperability Through Semantic Integration of Models with Ontologies—0
Drug response prediction by inferring pathway-response associations with Kernelized Bayesian Matrix Factorization—0
Dynamical models for metabolomics data integration—0
Dynamic Basis Function Interpolation for Adaptive In Situ Data Integration in Ocean Modeling—0
Easy Semantification of Bioassays—0
Efficient Joinable Table Discovery in Data Lakes: A High-Dimensional Similarity-Based Approach—0
Embedding-based Multimodal Learning on Pan-Squamous Cell Carcinomas for Improved Survival Outcomes—0
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