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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 351–360 of 431 papers

TitleStatusHype
Profiling Entity Matching Benchmark TasksCode0
Multifaceted Context Representation using Dual Attention for Ontology Alignment—0
Survive the Schema Changes: Integration of Unmanaged Data Using Deep Learning—0
BayReL: Bayesian Relational Learning for Multi-omics Data IntegrationCode1
LEAPME: Learning-based Property Matching with Embeddings—0
SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph SummarizationCode1
Kernel learning approaches for summarising and combining posterior similarity matricesCode0
Towards a Modular Ontology for Space Weather Research—0
Proceedings 36th International Conference on Logic Programming (Technical Communications)—0
Understanding Reflection Needs for Personal Health Data in Diabetes—0
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