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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 291300 of 431 papers

TitleStatusHype
Interactive Ontology Matching with Cost-Efficient Learning0
Interpretable graph-based models on multimodal biomedical data integration: A technical review and benchmarking0
IoT-Based 3D Pose Estimation and Motion Optimization for Athletes: Application of C3D and OpenPose0
IoT-Based Preventive Mental Health Using Knowledge Graphs and Standards for Better Well-Being0
It's AI Match: A Two-Step Approach for Schema Matching Using Embeddings0
KcMF: A Knowledge-compliant Framework for Schema and Entity Matching with Fine-tuning-free LLMs0
KnowGraph-PM: a Knowledge Graph based Pricing Model for Semiconductors Supply Chains0
Knowledge Graph Reasoning Based on Attention GCN0
Knowledge Graph Representations to enhance Intensive Care Time-Series Predictions0
Knowledge Graphs: The Future of Data Integration and Insightful Discovery0
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